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  • 1701.
    Wallenberg, Marcus
    et al.
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Forssén, Per-Erik
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Improving Random Forests by Correlation-Enhancing Projections and Sample-Based Sparse Discriminant Selection2016Ingår i: Proceedings 13th Conference on Computer and Robot Vision CRV 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, s. 222-227Konferensbidrag (Refereegranskat)
    Abstract [en]

    Random Forests (RF) is a learning techniquewith very low run-time complexity. It has found a nicheapplication in situations where input data is low-dimensionaland computational performance is paramount. We wish tomake RFs more useful for high dimensional problems, andto this end, we propose two extensions to RFs: Firstly, afeature selection mechanism called correlation-enhancing pro-jections, and secondly sparse discriminant selection schemes forbetter accuracy and faster training. We evaluate the proposedextensions by performing age and gender estimation on theMORPH-II dataset, and demonstrate near-equal or improvedestimation performance when using these extensions despite aseventy-fold reduction in the number of data dimensions.

  • 1702.
    Walter, F.
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys. Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Synthetic Aperture Radar2000Rapport (Övrigt vetenskapligt)
  • 1703.
    Wang, Chunliang
    Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Bildmedicinskt centrum, Röntgenkliniken i Linköping.
    Computer Assisted Coronary CT Angiography Analysis: Disease-centered Software Development2009Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    The substantial advances of coronary CTA have resulted in a boost of use of this new technique in the last several years, which brings a big challenge to radiologists by the increasing number of exams and the large amount of data for each patient. The main goal of this study was to develop a computer tool to facilitate coronary CTA analysis by combining knowledge of medicine and image processing.Firstly, a competing fuzzy connectedness tree algorithm was developed to segment the coronary arteries and extract centerlines for each branch. The new algorithm, which is an extension of the “virtual contrast injection” method, preserves the low density soft tissue around the coronary, which reduces the possibility of introducing false positive stenoses during segmentation.Secondly, this algorithm was implemented in open source software in which multiple visualization techniques were integrated into an intuitive user interface to facilitate user interaction and provide good over¬views of the processing results. Considerable efforts were put on optimizing the computa¬tional speed of the algorithm to meet the clinical requirements.Thirdly, an automatic seeding method, that can automatically remove rib cage and recognize the aortic root, was introduced into the interactive segmentation workflow to further minimize the requirement of user interactivity during post-processing. The automatic procedure is carried out right after the images are received, which saves users time after they open the data. Vessel enhance¬ment and quantitative 2D vessel contour analysis are also included in this new version of the software. In our preliminary experience, visually accurate segmentation results of major branches have been achieved in 74 cases (42 cases reported in paper II and 32 cases in paper III) using our software with limited user interaction. On 128 branches of 32 patients, the average overlap between the centerline created in our software and the manually created reference standard was 96.0%. The average distance between them was 0.38 mm, lower than the mean voxel size. The automatic procedure ran for 3-5 min as a single-thread application in the background. Interactive processing took 3 min in average with the latest version of software. In conclusion, the presented software provides fast and automatic coron¬ary artery segmentation and visualization. The accuracy of the centerline tracking was found to be acceptable when compared to manually created centerlines.

  • 1704.
    Wang, Chunliang
    Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Hälsouniversitetet.
    Computer-­Assisted  Coronary  CT  Angiography  Analysis: From  Software  Development  to  Clinical  Application2011Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Advances in coronary Computed Tomography Angiography (CTA) have resulted in a boost in the use of this new technique in recent years, creating a challenge for radiologists due to the increasing number of exams and the large amount of data for each patient. The main goal of this study was to develop a computer tool to facilitate coronary CTA analysis by combining knowledge of medicine and image processing, and to evaluate the performance in clinical settings.

    Firstly, a competing fuzzy connectedness tree algorithm was developed to segment the coronary arteries and extract centerlines for each branch. The new algorithm, which is an extension of the “virtual contrast injection” (VC) method, preserves the low-density soft tissue around the artery, and thus reduces the possibility of introducing false positive stenoses during segmentation. Visually reasonable results were obtained in clinical cases.

    Secondly, this algorithm was implemented in open source software in which multiple visualization techniques were integrated into an intuitive user interface to facilitate user interaction and provide good over­views of the processing results. An automatic seeding method was introduced into the interactive segmentation workflow to eliminate the requirement of user initialization during post-processing. In 42 clinical cases, all main arteries and more than 85% of visible branches were identified, and testing the centerline extraction in a reference database gave results in good agreement with the gold standard.

    Thirdly, the diagnostic accuracy of coronary CTA using the segmented 3D data from the VC method was evaluated on 30 clinical coronary CTA datasets and compared with the conventional reading method and a different 3D reading method, region growing (RG), from a commercial software. As a reference method, catheter angiography was used. The percentage of evaluable arteries, accuracy and negative predictive value (NPV) for detecting stenosis were, respectively, 86%, 74% and 93% for the conventional method, 83%, 71% and 92% for VC, and 64%, 56% and 93% for RG. Accuracy was significantly lower for the RG method than for the other two methods (p<0.01), whereas there was no significant difference in accuracy between the VC method and the conventional method (p = 0.22).

    Furthermore, we developed a fast, level set-based algorithm for vessel segmentation, which is 10-20 times faster than the conventional methods without losing segmentation accuracy. It enables quantitative stenosis analysis at interactive speed.

    In conclusion, the presented software provides fast and automatic coron­ary artery segmentation and visualization. The NPV of using only segmented 3D data is as good as using conventional 2D viewing techniques, which suggests a potential of using them as an initial step, with access to 2D reviewing techniques for suspected lesions and cases with heavy calcification. Combining the 3D visualization of segmentation data with the clinical workflow could shorten reading time.

  • 1705.
    Wang, Chunliang
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. KTH Royal Institute Technology, Sweden; Sectra AB, S-58330 Linkoping, Sweden.
    Dahlström, Nils
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Region Östergötland, Diagnostikcentrum, Röntgenkliniken i Linköping. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Fransson, Sven Göran
    Region Östergötland, Diagnostikcentrum, Röntgenkliniken i Linköping. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper.
    Lundström, Claes
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Smedby, Örjan
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Region Östergötland, Diagnostikcentrum, Röntgenkliniken i Linköping. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. KTH Royal Institute Technology, Sweden.
    Real-Time Interactive 3D Tumor Segmentation Using a Fast Level-Set Algorithm2015Ingår i: Journal of Medical Imaging and Health Informatics, ISSN 2156-7018, E-ISSN 2156-7026, Vol. 5, nr 8, s. 1998-2002Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A new level-set based interactive segmentation framework is introduced, where the algorithm learns the intensity distributions of the tumor and surrounding tissue from a line segment drawn by the user from the middle of the lesion towards the border. This information is used to design a likelihood function, which is then incorporated into the level-set framework as an external speed function guiding the segmentation. The endpoint of the input line segment sets a limit to the propagation of 3D region, i.e., when the zero-level-set crosses this point, the propagation is forced to stop. Finally, a fast level set algorithm with coherent propagation is used to solve the level set equation in real time. This allows the user to instantly see the 3D result while adjusting the position of the line segment to tune the parameters implicitly. The "fluctuating" character of the coherent propagation also enables the contour to coherently follow the mouse cursors motion when the user tries to fine-tune the position of the contour on the boundary, where the learned likelihood function may not necessarily change much. Preliminary results suggest that radiologists can easily learn how to use the proposed segmentation tool and perform relatively accurate segmentation with much less time than the conventional slice-by-slice based manual procedure.

  • 1706.
    Wang, Chunliang
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Sectra, Linkoping, Sweden.
    Forsberg, Daniel
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Sectra, Linkoping, Sweden.
    Segmentation of Intervertebral Discs in 3D MRI Data Using Multi-atlas Based Registration2016Ingår i: Computational Methods and Clinical Applications for Spine Imaging, CSI 2015, SPRINGER INT PUBLISHING AG , 2016, Vol. 9402, s. 107-116Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents one of the participating methods to the intervertebral disc segmentation challenge organized in conjunction with the 3rd MICCAI Workshop amp; Challenge on Computational Methods and Clinical Applications for Spine Imaging - MICCAI-CSI2015. The presented method consist of three steps. In the first step, vertebral bodies are detected and labeled using integral channel features and a graphical parts model. The second step consists of image registration, where a set of image volumes with corresponding intervertebral disc atlases are registered to the target volume using the output from the first step as initialization. In the final step, the registered atlases are combined using label fusion to derive the final segmentation. The pipeline was evaluated using a set of 15 + 10 T2-weighted image volumes provided as training and test data respectively for the segmentation challenge. For the training data, a mean disc centroid distance of 0.86 mm and an average DICE score of 91% was achieved, and for the test data the corresponding results were 0.90 mm and 90%.

  • 1707.
    Wang, Chunliang
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Frimmel, Hans
    Institutionen för informationteknologi, Uppsala universitet, Sweden.
    Persson, Anders
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Bildmedicinskt centrum, Röntgenkliniken i Linköping.
    Smedby, Örjan
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Bildmedicinskt centrum, Röntgenkliniken i Linköping.
    An interactive software module for visualizing coronary arteries in CT angiography2008Ingår i: International Journal of Computer Assisted Radiology and Surgery, ISSN 1861-6410, Vol. 3, nr 1-2, s. 11-18Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A new software module for coronary artery segmentation and visualization in CT angiography (CTA) datasets is presented, which aims to interactively segment coronary arteries and visualize them in 3D with maximum intensity projection (MIP) and volume rendering (VRT).

    Materials and Methods:  The software was built as a plug-in for the open-source PACS workstation OsiriX. The main segmentation function is based an optimized “virtual contrast injection” algorithm, which uses fuzzy connectedness of the vessel lumen to separate the contrast-filled structures from each other. The software was evaluated in 42 clinical coronary CTA datasets acquired with 64-slice CT using isotropic voxels of 0.3–0.5 mm.

    Results:  The median processing time was 6.4 min, and 100% of main branches (right coronary artery, left circumflex artery and left anterior descending artery) and 86.9% (219/252) of visible minor branches were intact. Visually correct centerlines were obtained automatically in 94.7% (321/339) of the intact branches.

    Conclusion:  The new software is a promising tool for coronary CTA post-processing providing good overviews of the coronary artery with limited user interaction on low-end hardware, and the coronary CTA diagnosis procedure could potentially be more time-efficient than using thin-slab technique.

  • 1708.
    Wang, Chunliang
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Smedby, Örjan
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Region Östergötland, Diagnostikcentrum, Röntgenkliniken i Linköping.
    An Automatic Seeding Method For Coronary Artery Segmentation and Skeletonization in CTA2008Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    An automatic seeding method for coronary artery segmentation and skeletonization is presented. The new method includes automatic removal of the rib cage, tracing of the ascending aorta and initial planting of seeds for the coronary arteries. The automatic seeds are then passed on to a “virtual contrast injection” algorithm performing segmentation and skeletonization. In preliminary experiments, most main branches of the coronary tree were segmented and skeletonized without any user interaction.

  • 1709.
    Wang, Chunliang
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Smedby, Örjan
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Bildmedicinskt centrum, Röntgenkliniken i Linköping.
    Coronary Artery Segmentation and Skeletonization Based on Competing Fuzzy Connectedness Tree2007Ingår i: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007: 10th International Conference, Brisbane, Australia, October 29 - November 2, 2007, Proceedings, Part I / [ed] Nicholas Ayache, Sébastien Ourselin, Anthony Maeder, Springer Berlin/Heidelberg, 2007, Vol. 4791, s. 311-318Konferensbidrag (Refereegranskat)
    Abstract [en]

    We propose a new segmentation algorithm based on competing fuzzy connectedness theory, which is then used for visualizing coronary arteries in 3D CT angiography (CTA) images. The major difference compared to other fuzzy connectedness algorithms is that an additional data structure, the connectedness tree, is constructed at the same time as the seeds propagate. In preliminary evaluations, accurate result have been achieved with very limited user interaction. In addition to improving computational speed and segmentation results, the fuzzy connectedness tree algorithm also includes automated extraction of the vessel centerlines, which is a promising approach for creating curved plane reformat (CPR) images along arteries’ long axes.

  • 1710.
    Wang, Chunliang
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Smedby, Örjan
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Region Östergötland, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Fully automatic brain segmentation using model-guided level set and skeleton based models2013Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    A fully automatic brain segmentation method is presented. First the skull is stripped using a model-based level set on T1-weighted inversion recovery images, then the brain ventricles and basal ganglia are segmented using the same method on T1-weighted images. The central white matter is segmented using a regular level set method but with high curvature regulation. To segment the cortical gray matter, a skeleton-based model is created by extracting the mid-surface of the gray matter from a preliminary segmentation using a threshold-based level set. An implicit model is then built by defining the thickness of the gray matter to be 2.7 mm. This model is incorporated into the level set framework and used to guide a second round more precise segmentation. Preliminary experiments show that the proposed method can provide relatively accurate results compared with the segmentation done by human observers. The processing time is considerably shorter than most conventional automatic brain segmentation methods.

  • 1711.
    Wang, Chunliang
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Smedby, Örjan
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Bildmedicinskt centrum, Röntgenkliniken i Linköping.
    Integrating automatic and interactive method for coronary artery segmentation: let PACS workstation think ahead2010Ingår i: International Journal of Computer Assisted Radiology and Surgery, ISSN 1861-6410, E-ISSN 1861-6429, Vol. 5, nr 3, s. 275-285Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Purpose: To provide an efficient method to extract useful information from the increasing amount of coronary CTA.

    Methods: A quantitative coronary CTA analysis tool was built on OsiriX, which integrates both fully automatic and interactive methods for coronary artery extraction. The computational power of an ordinary PC is exploited by running the non-supervised coronary artery segmentation and centerline tracking in the background as soon as the images are received. When the user opens the data, the software provides a real-time interactive analysis environment.

    Results: The average overlap between the centerline created in our software and the reference standard was 96.0%. The average distance between them was 0.38 mm. The automatic procedure runs for 3-5 min as a single-thread application in background. Interactive processing takes 3 min in average.

    Conclusion: In preliminary experiments, the software achieved higher efficiency than the former interactive method, and reasonable accuracy compared to manual vessel extraction.

  • 1712.
    Wang, Gaihua
    et al.
    Hubei Collaborative Innovation Centre for High-efficiency Utilization of Solar Energy, Hubei University of Technology, China / School of Electrical and Electronic Engineering, Hubei University of Technology, China.
    Liu, Yang
    School of Electrical and Electronic Engineering, Hubei University of Technology, China / Faculty of Technology, University of Vaasa, Vaasa, Finland.
    Xiong, Caiquan
    School of Computer Science, Hubei University of Technology, China.
    An Optimization Clustering Algorithm Based on Texture Feature Fusion for Color Image Segmentation2015Ingår i: Algorithms, ISSN 1999-4893, E-ISSN 1999-4893, Vol. 8, nr 2, s. 234-247Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We introduce a multi-feature optimization clustering algorithm for color image segmentation. The local binary pattern, the mean of the min-max difference, and the color components are combined as feature vectors to describe the magnitude change of grey value and the contrastive information of neighbor pixels. In clustering stage, it gets the initial clustering center and avoids getting into local optimization by adding mutation operator of genetic algorithm to particle swarm optimization. Compared with well-known methods, the proposed method has an overall better segmentation performance and can segment image more accurately by evaluating the ratio of misclassification.

  • 1713.
    Wang, Gaihua
    et al.
    School of Electrical and Electronic Engineering, Hubei University of Technology, China.
    Liu, Yang
    School of Electrical and Electronic Engineering, Hubei University of Technology, China / Faculty of Technology, University of Vaasa, Vaasa, Finland.
    Zhao, Tongzhou
    Hubei Province Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, China.
    A quaternion-based switching filter for colour image denoising2014Ingår i: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 102, s. 216-225Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    An improved quaternion switching filter for colour image denoising is presented. It proposes a RGB colour image as a pure quaternion form and measures differences between two colour pixels with the quaternion-based distance. Further, in noise-detection, a two-stage detection method is proposed to determine whether the current pixel is noise or not. The noisy pixels are replaced by the vector median filter (VMF) output and the noise-free ones are unchanged. Finally, we combine the advantages of quaternion-based switching filter and non-local means filter to remove mixture noise. By comparing the performance and computing time processing different images, the proposed method has superior performance which not only provides the best noise suppression results but also yields better image quality compared to other widely used filters.

  • 1714. Wang, L.
    et al.
    Wang, X.
    Hu, Xiaoming
    KTH, Skolan för teknikvetenskap (SCI), Matematik (Inst.), Optimeringslära och systemteori.
    Distributed tracking and connectivity maintenance with a varying velocity leader2012Ingår i: 2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012, IEEE , 2012, s. 1824-1829Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper investigates a distributed tracking problem for multi-agent systems with a varying-velocity leader. The leader modeled by a double integrator can only be perceived by followers located within a sensing distance. The objective is to drive the followers with bounded control law to maintain connectivity, avoid collision and further track the leader, with no need of acceleration measurements. Two cases are considered: the acceleration of the leader is bounded; and the acceleration has a linear form. In the first case, the relative velocities of neighbors are integrated and transmitted as a new variable to account for the uncertain time-varying acceleration. In the second case, two distributed estimators are added for the leader's position and velocity. Simulations are presented to show the effectiveness of the proposed control laws.

  • 1715.
    Wang, Wei
    et al.
    KTH, Skolan för arkitektur och samhällsbyggnad (ABE), Samhällsplanering och miljö, Geoinformatik.
    Zhai, Qinglin
    Natl Univ Def Technol, Coll Elect Sci & Engn, Changsha 410073, Hunan, Peoples R China..
    Ban, Yifang
    KTH, Skolan för arkitektur och samhällsbyggnad (ABE), Samhällsplanering och miljö, Geoinformatik.
    Zhang, Jun
    Natl Univ Def Technol, Coll Elect Sci & Engn, Changsha 410073, Hunan, Peoples R China..
    Wan, Jianwei
    Natl Univ Def Technol, Coll Elect Sci & Engn, Changsha 410073, Hunan, Peoples R China..
    POLSAR IMAGE SEGMENTATION BASED ON HIERARCHICAL REGION MERGING AND SEGMENT REFINEMENT WITH WMRF MODEL2017Ingår i: 2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), IEEE , 2017, s. 4574-4577Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper, a superpixel-based segmentation method is proposed for PolSAR images by utilizing hierarchical region merging and segment refinement. The loss of the energy function, which determines the consistency of two adjacent regions from the statistical aspect, is applied to guide the merging procedure. In addition to the edge penalty term, the homogeneity measurement is also employed to prevent merging the regions that are from different land covers or objects. Based on the merged segments, the segment refinement is applied to further improve the segmentation accuracy by iteratively relabeling the edge pixels. It uses a maximum a posterior (MAP) criterion using the statistical distribution of the pixels and the Markov random field (MRF) model. The performance of the proposed method is validated on an experimental PolSAR dataset from the ESAR system.

  • 1716.
    Wang Weixing, Bergholm Fredrik
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys. Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Froth delineation based on image classification2003Ingår i: Minerals engineeringArtikel i tidskrift (Övrigt vetenskapligt)
  • 1717.
    Wang, Weixing
    et al.
    KTH, Skolan för informations- och kommunikationsteknik (ICT). Collage of Physics and Information Engineering, Fuzhou University, Fuzhou, Fujian, China.
    Liang, Y.
    Rock fracture centerline extraction based on hessian matrix and steger algorithm2015Ingår i: KSII Transactions on Internet and Information Systems, ISSN 1976-7277, Vol. 9, nr 12, s. 5073-5086Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The rock fracture detection by image analysis is significant for fracture measurement and assessment engineering. The paper proposes a novel image segmentation algorithm for the centerline tracing of a rock fracture based on Hessian Matrix at Multi-scales and Steger algorithm. A traditional fracture detection method, which does edge detection first, then makes image binarization, and finally performs noise removal and fracture gap linking, is difficult for images of rough rock surfaces. To overcome the problem, the new algorithm extracts the centerlines directly from a gray level image. It includes three steps: (1) Hessian Matrix and Frangi filter are adopted to enhance the curvilinear structures, then after image binarization, the spurious-fractures and noise are removed by synthesizing the area, circularity and rectangularity; (2) On the binary image, Steger algorithm is used to detect fracture centerline points, then the centerline points or segments are linked according to the gap distance and the angle differences; and (3) Based on the above centerline detection roughly, the centerline points are searched in the original image in a local window along the direction perpendicular to the normal of the centerline, then these points are linked. A number of rock fracture images have been tested, and the testing results show that compared to other traditional algorithms, the proposed algorithm can extract rock fracture centerlines accurately.

  • 1718.
    Wang, Xuerui
    et al.
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Zhao, Li
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Navigation and Automatic Ground Mapping by Rover Robot2010Självständigt arbete på avancerad nivå (masterexamen), 30 poäng / 45 hpStudentuppsats (Examensarbete)
    Abstract [en]

    This project is mainly based on mosaicing of images and similarity measurements with different methods. The map of a floor is created from a database of small-images that have been captured by a camera-mounted robot scanning the wooden floor of a living room. We call this ground mapping. After the ground mapping, the robot can achieve self-positioning on the map by using novel small images it captures as it displaces on the ground. Similarity measurements based on the Schwartz inequality have been used to achieve the ground mapping, as well as to position the robot once the ground map is available. Because the natural light affects the gray value of images, this effect must be accounted for in the envisaged similarity measurements. A new approach to mosaicing is suggested. It uses the local texture orientation, instead of the original gray values, in ground mapping as well as in positioning. Additionally, we report on ground mapping results using other features, gray-values as features. The robot can find its position with few pixel errors by using the novel approach and similarity measurements based on the Schwartz inequality.

  • 1719.
    Wang, Yuquan
    et al.
    KTH, Skolan för industriell teknik och management (ITM), Industriell produktion.
    Liu, Hongyi
    KTH, Skolan för industriell teknik och management (ITM), Industriell produktion.
    Ji, Wei
    KTH, Skolan för industriell teknik och management (ITM), Industriell produktion.
    Wang, Wei
    KTH, Skolan för industriell teknik och management (ITM), Industriell produktion.
    Realtime collaborating with an industrial manipulator using a constraint-based programming approach2018Ingår i: 51st CIRP Conference on Manufacturing Systems, Elsevier, 2018, s. 105-110Konferensbidrag (Refereegranskat)
    Abstract [en]

    Safety is the first and foremost step on our long journey to a future in which robots are moving out of the cage to collaborate with and assist people in various fields from entertainment to manufacturing. Different from the well-defined structured environment, safe robot control in a workspace with moving objects, e.g. a human, requires us to control the robot motion on the fly. In order to computationally efficiently achieve a feasible solution, we propose a constraint-based programming approach to guarantee the safe human-robot interaction. We use an optimization framework to integrate constraints from two-fold: the robot control constraints that are responsible for a generic robotic task and the online formulated safety constraints that are responsible for safe human-robot interaction. In this way, we preserve the task execution ability of a robot while guarantee the safe human-robot interaction. We validate the proposed approach with a Schunk industrial manipulator. The experimental results confirms the fact that the proposed approach has the potential to enable an industrial manipulator to work with a human coworker side-by-side.

  • 1720.
    Wasik, Alicja
    et al.
    Distributed Intelligent Systems and Algorithms Laboratory, School of Archiecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Switzerland.
    Tomic, Stevan
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Martinoli, Alcherio
    Distributed Intelligent Systems and Algorithms Laboratory, School of Archiecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Switzerland.
    Lima, Pedro U.
    Institute for Systems and Robotics, Instituto Superior Técnico, Universidade de Lisboa, Portugal.
    Towards Norm Realization in Institutions Mediating Human-Robot Societies2018Ingår i: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE , 2018, s. 297-304Konferensbidrag (Refereegranskat)
    Abstract [en]

    Social norms are the understandings that govern the behavior of members of a society. As such, they regulate communication, cooperation and other social interactions. Robots capable of reasoning about social norms are more likely to be recognized as an extension of our human society. However, norms stated in a form of the human language are inherently vague and abstract. This allows for applying norms in a variety of situations, but if the robots are to adhere to social norms, they must be capable of translating abstract norms to the robotic language. In this paper we use a notion of institution to realize social norms in real robotic systems. We illustrate our approach in a case study, where we translate abstract norms into concrete constraints on cooperative behaviors of humans and robots. We investigate the feasibility of our approach and quantitatively evaluate the performance of our framework in 30 real experiments with user-based evaluation with 40 participants.

  • 1721.
    Wedberg, Magnus
    Linköpings universitet, Institutionen för systemteknik, Datorseende.
    Detecting Rails in Images from a Train-Mounted Thermal Camera Using a Convolutional Neural Network2017Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Now and then train accidents occur. Collisions between trains and objects such as animals, humans, cars, and fallen trees can result in casualties, severe damage on the train, and delays in the train traffic. Thus, train collisions are a considerable problem with consequences affecting society substantially.

    The company Termisk Systemteknik AB has on commission by Rindi Solutions AB investigated the possibility to detect anomalies on the railway using a trainmounted thermal imaging camera. Rails are also detected in order to determine if an anomaly is on the rail or not. However, the rail detection method does not work satisfactory at long range.

    The purpose of this master’s thesis is to improve the previous rail detector at long range by using machine learning, and in particular deep learning and a convolutional neural network. Of interest is also to investigate if there are any advantages using cross-modal transfer learning.

    A labelled dataset for training and testing was produced manually. Also, a loss function tailored to the particular problem at hand was constructed. The loss function was used both for improving the system during training and evaluate the system’s performance during testing. Finally, eight different approaches were evaluated, each one resulting in a different rail detector.

    Several of the rail detectors, and in particular all the rail detectors using crossmodal transfer learning, perform better than the previous rail detector. Thus, the new rail detectors show great potential to the rail detection problem.

  • 1722.
    Wehrmann, Felix
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys.
    On Modelling Nonlinear Variation in Discrete Appearances of Objects2004Doktorsavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    Mathematical models of classes of objects can significantly contribute to the analysis of digital images. A major problem in modelling is to establish suitable descriptions that cover not only a single object but also the variation that is usually present within a class of objects.

    The objective of this thesis is to develop more general modelling strategies than commonly used today. In particular, the impact of the human factor in the model creation process should be minimised. It is presumed that the human ability of abstraction imposes undesired constraints on the description. In comparison, common approaches are discussed from the viewpoint of generality.

    The technique considered introduces appearance space as a common framework to represent both shapes and images. In appearance space, an object is represented by a single point in a high-dimensional vector space. Accordingly, objects subject to variation appear as nonlinear manifolds in appearance space. These manifolds are often characterised by only a few intrinsic dimensions. A model of a class of objects is therefore considered equal to the mathematical description of this manifold.

    The presence of nonlinearity motivates the use of artificial auto-associative neural networks in the modelling process. The network extracts nonlinear modes of variation from a number of training examples. The procedure is evaluated on both synthetic and natural data of shapes and images and shows promising results as a general approach to object modelling.

  • 1723.
    Wehrmann, Felix
    et al.
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys. Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Bengtsson, Ewert
    Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Modelling non-linearities in images using an auto-associativeneural network2003Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper, we address non-linearities in images to approach

  • 1724.
    Wehrmann, Felix
    et al.
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys. Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Bengtsson, Ewert
    Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Modelling of shapes without landmarks2003Konferensbidrag (Refereegranskat)
    Abstract [en]

    The complexity in variation that objects are provided with motivates to consider learning strategies when modeling their shape. This paper evaluates auto-associative neural networks and their application to shape analysis. Previously, such networks have b

  • 1725. Wei, Yangjie
    et al.
    Wu, Chengdong
    Yi, Wang
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datorteknik.
    Dong, Zaili
    Efficient shape reconstruction of microlens using optical microscopy2015Ingår i: IEEE transactions on industrial electronics (1982. Print), ISSN 0278-0046, E-ISSN 1557-9948, Vol. 62, nr 12, s. 7655-7664Artikel i tidskrift (Refereegranskat)
  • 1726. Wei, Yangjie
    et al.
    Wu, Chengdong
    Yi, Wang
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datorteknik.
    Wang, Wenxue
    Diffusion-based three-dimensional reconstruction of complex surface using monocular vision2015Ingår i: Optics Express, ISSN 1094-4087, E-ISSN 1094-4087, Vol. 23, nr 23, s. 30364-30378Artikel i tidskrift (Refereegranskat)
  • 1727.
    Weistrand, Ola
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Matematiska institutionen. Fakultetsövergripande enheter, Centrum för bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Matematiska institutionen, Matematik I-5.
    Shape approximation of discrete starshaped objects2006Ingår i: Pattern Recognition Letters, Vol. 27, nr 16, s. 1934-1941Artikel i tidskrift (Refereegranskat)
  • 1728.
    Welle, Michael
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Ericson, Ludvig
    KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Ambrus, Rares
    KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Jensfelt, Patric
    KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    On the use of Unmanned Aerial Vehicles for Autonomous Object Modeling2017Ingår i: 2017 European Conference on Mobile Robots, ECMR 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, artikel-id 8098656Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we present an end to end object modeling pipeline for an unmanned aerial vehicle (UAV). We contribute a UAV system which is able to autonomously plan a path, navigate, acquire views of an object in the environment from which a model is built. The UAV does collision checking of the path and navigates only to those areas deemed safe. The data acquired is sent to a registration system which segments out the object of interest and fuses the data. We also show a qualitative comparison of our results with previous work.

  • 1729.
    Wen, Wei
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kommunikationssystem.
    Khatibi, Siamak
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kommunikationssystem.
    Towards Measuring of Depth Perception from Monocular Shadow Technique with Application in a Classical Painting2016Ingår i: Journal of Computers, ISSN 1796-203X, Vol. 11, s. 310-319Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Depth perception is one of important abilities of the human visual system to perceive the three dimensional world. Shadow technique that offers different depth information from different viewing points, known as Da Vinci stereopsis, has been used in classical paintings. In this paper, we report a method towards measuring the relative depth information stimulated by Da Vinci stereopsis in a classical painting. We set up a positioning array of cameras for capturing images from the portrait using a high resolution camera, where the changes of shadow areas are measured by featuring the effects as point and line changes. The result shows that 3D effects of the classical painting are not only a perceptual phenomenon but they are also physically tangible and can be measured. We confirm validity of the method by its implementation even on a typical single image and comparison of results between the single image and the portrait.

  • 1730.
    Wen, Wei
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för teknik och estetik.
    Siamak, Khatibi
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för teknik och estetik.
    Estimation of Image Sensor Fill Factor Using a Single Arbitrary Image2017Ingår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 17, nr 3, s. 620-Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Achieving a high fill factor is a bottleneck problem for capturing high-quality images. There are hardware and software solutions to overcome this problem. In the solutions, the fill factor is known. However, this is an industrial secrecy by most image sensor manufacturers due to its direct effect on the assessment of the sensor quality. In this paper, we propose a method to estimate the fill factor of a camera sensor from an arbitrary single image. The virtual response function of the imaging process and sensor irradiance are estimated from the generation of virtual images. Then the global intensity values of the virtual images are obtained, which are the result of fusing the virtual images into a single, high dynamic range radiance map. A non-linear function is inferred from the original and global intensity values of the virtual images. The fill factor is estimated by the conditional minimum of the inferred function. The method is verified using images of two datasets. The results show that our method estimates the fill factor correctly with significant stability and accuracy from one single arbitrary image according to the low standard deviation of the estimated fill factors from each of images and for each camera.

  • 1731.
    Wernersson, Björn
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Södergren, Mikael
    Linköpings universitet, Institutionen för systemteknik.
    Automatiserad inlärning av detaljer för igenkänning och robotplockning2005Självständigt arbete på avancerad nivå (magisterexamen), 20 poäng / 30 hpStudentuppsats
    Abstract [en]

    Just how far is it possible to make learning of new parts for recognition and robot picking autonomous? This thesis initially gives the prerequisites for the steps in learning and calibration that are to be automated. Among these tasks are to select a suitable part model from numerous candidates with the help of a new part segmenter, as well as computing the spatial extent of this part, facilitating robotic collision handling. Other tasks are to analyze the part model in order to highlight correct and suitable edge segments for increasing pattern matching certainty, and to choose appropriate acceptance levels for pattern matching. Furthermore, tasks deal with simplifying camera calibration by analyzing the calibration pattern, as well as compensating for differences in perspective at great depth variations, by calculating the centre of perspective of the image. The image processing algorithms created in order to solve the tasks are described and evaluated thoroughly. This thesis shows that simplification of steps of learning and calibration, by the help of advanced image processing, really is possible.

  • 1732.
    Wernersson, Erik
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Centrum för bildanalys.
    Brun, Anders
    Luengo Hendriks, Cris L
    Closing pores and  segmenting individual fibres in 3{D} images of wood fibre composites using curvature information and graph cuts2009Ingår i: SSBA Symposium on Image Analysis 2009 / [ed] Josef Bigun and Antanas Verikas, 2009, s. 113-116Konferensbidrag (Övrigt vetenskapligt)
  • 1733.
    Wernersson, Erik
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Centrum för bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Brun, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Centrum för bildanalys.
    Luengo Hendriks, Cris L.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Centrum för bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Segmentation of Wood Fibres in 3D CT Images Using Graph Cuts2009Ingår i: Image Analysis and Processing – ICIAP 2009, Berlin: Springer-Verlag , 2009, s. 92-102Konferensbidrag (Refereegranskat)
    Abstract [en]

    To completely segment all individual wood fibres in volume images of fibrous materials presents a challenging problem but is important in understanding the micro mechanical properties of composite materials. This paper presents a filter that identifies and closes pores in wood fibre walls, simplifying the shape of the fibres. After this filter, a novel segmentation method based on graph cuts identifies individual fibres. The methods are validated on a realistic synthetic fibre data set and then applied on μCT images of wood fibre composites.

  • 1734.
    Wernersson, Erik L. G.
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Centrum för bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Luengo Hendriks, Cris L.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Centrum för bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Brun, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Centrum för bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Accurate estimation of Gaussian and mean curvature in volumetric images2011Ingår i: International Conference on 3D Imaging, Modeling, Processing, Visualization, and Transmission, 3DIMPVT 2011, IEEE Publications , 2011, s. 312-317Konferensbidrag (Refereegranskat)
  • 1735.
    Wernersson, Erik L. G.
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Centrum för bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Luengo Hendriks, Cris L.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Centrum för bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Brun, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Centrum för bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Calculating curvature from orientation fields in volumetric images2011Konferensbidrag (Övrigt vetenskapligt)
  • 1736.
    Wernersson, Erik
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Centrum för bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Luengo Hendriks, Cris L.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Centrum för bildanalys.
    Brun, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Centrum för bildanalys.
    Generating synthetic μCT images of wood fibre materials2009Ingår i: Proc. 6th International Symposium on Image and Signal Processing and Analysis: ISPA 2009, Piscataway, NJ: IEEE , 2009, s. 365-370Konferensbidrag (Refereegranskat)
    Abstract [en]

    X-ray Computerized Tomography at micrometer resolution (μCT) is an important tool for understanding the properties of wood fibre materials such as paper, carton and wood fibre composites. While many image analysis methods have been developed for μCT images in wood science, the evaluation of these methods if often not thorough enough because of the lack of a dataset with ground truth. This paper describes the generation of synthetic μCT volumes of wood fibre materials. Fibres with a high degree of morphological variations are modeled and densely packed into a volume of the material. Using a simulation of the μCT image acquisition process, realistic synthetic images are obtained. This simulation uses noise characterized from a set of μCT images. The synthetic images have a known ground truth, and can therefore be used when evaluating image analysis methods.

  • 1737.
    Westberg, Michael
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Time of Flight Based Teat Detection2009Självständigt arbete på avancerad nivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Time of flight is an imaging technique with uses depth information to capture 3D information in a scene. Recent developments in the technology have made ToF cameras more widely available and practical to work with. The cameras now enable real time 3D imaging and positioning in a compact unit, making the technology suitable for variety of object recognition tasks

    An object recognition system for locating teats is at the center of the DeLaval VMS, which is a fully automated system for milking cows. By implementing ToF technology as part of the visual detection procedure, it would be possible to locate and track all four teat’s positions in real time and potentially provide an improvement compared with the current system.

    The developed algorithm for teat detection is able to locate teat shaped objects in scenes and extract information of their position, width and orientation. These parameters are determined with an accuracy of millimeters. The algorithm also shows promising results when tested on real cows. Although detecting many false positives the algorithm was able to correctly detected 171 out of 232 visible teats in a test set of real cow images. This result is a satisfying proof of concept and shows the potential of ToF technology in the field of automated milking.

  • 1738.
    Wester, K
    et al.
    Uppsala universitet, Fakultetsövergripande enheter, Centrum för bildanalys. Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Andersson, AC
    Ranefall, F
    Bengtsson, E
    Malmstrom, PU
    Busch, C
    Cultured human fibroblasts in agarose gel as a multi-functional control for immunohistochemistry. Standardization of Ki67 (MIBI) assessment in routinely processed urinary bladder carcinoma tissue2000Ingår i: JOURNAL OF PATHOLOGY, ISSN 0022-3417, Vol. 190, nr 4, s. 503-511Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Immunohistochemistry (IHC) in clinical practice is hampered by lack of standardization and by subjectivity in interpretation and quantitation, This study aimed to develop a control system for IHC in routinely fixed and histoprocessed tissues. Such a syste

  • 1739.
    Wester, K
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Centrum för bildanalys. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datoriserad bildanalys.
    Wahlund, E
    Sundstrom, C
    Ranefall, P
    Bengtsson, E
    Russell, PJ
    Ow, KT
    Malmstrom, PU
    Busch, C
    Paraffin section storage and immunohistochemistry - Effects of time, temperature, fixation, and retrieval protocol with emphasis on p53 protein and MIB1 antigen2000Ingår i: APPLIED IMMUNOHISTOCHEMISTRY & MOLECULAR MORPHOLOGY, ISSN 1062-3345, Vol. 8, nr 1, s. 61-70Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    It has been observed that immunoreactivity in paraffin sections decreased during storage. In this study, stored paraffin sections from both biopsy material and cultured cells were assessed for changes in immunoreactivity, using color-based image analysis

  • 1740.
    Westerberg, Simon
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Shiriaev, Anton S.
    Norwegian University of Science and Technology.
    Modeling of head orientation for applications in manipulator controlManuskript (preprint) (Övrigt vetenskapligt)
    Abstract [en]

    Many heavy equipment manipulators, such as those found on excavators and forestry machines, currently require continuous manual control. While full automation of these systems is complicated due to the unstructured environments in which they are used, semi-automation can be a useful tool for improving both efficiency and working conditions. In the case of forestry machines, we have located specific work tasks where recent advances in time efficient trajectory planning could be used to increase productivity. However, in order to fully take advantage of these methods, a user interface must be developed that will let the operators communicate their intentions to the system in an intuitive and efficient way. We therefore propose a novel interaction method where headtracking is used to estimate the operator’s gaze in order to specify a target point as input to the trajectory planner for the hydraulic manipulator. In this paper, we investigate the feasibility of such a system, through analysis of task-specific requirements. From dedicated user experiments done in a lab we have identified and tested a model from head orientation to gaze direction, which allows us to predict the gaze angle with an average accuracy of close to 4 degrees. In a field test we have verified that the method is transferable to a real-world setting with comparable results.

  • 1741.
    Westerberg, Simon
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Shiriaev, Anton S
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Virtual environment-based teleoperation of forestry machines: designing future interaction methods2013Ingår i: Journal of Human-Robot Interaction, ISSN 2163-0364, Vol. 2, nr 3, s. 84-110Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Virtual environment-assisted teleoperation has great potential as a human-robot interaction paradigm for field robotic systems, in particular when combined with elements of automation. Unstructured outdoor environments present a complex problem with many challenging elements. For the specific application of forestry machines, we investigate which steps are required in order to implement such a system, what potential benefits there are, and how individual components can be adapted to efficiently assist forestry machine operators in their daily work in the near future. An experimental prototype of a teleoperation system with virtual environment-based feedback is constructed using a scenario-based design process. The feasibility of the implementation is partly verified through experimental studies.

  • 1742.
    Westphal, Florian
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datalogi och datorsystemteknik.
    Efficient Document Image Binarization using Heterogeneous Computing and Interactive Machine Learning2018Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Large collections of historical document images have been collected by companies and government institutions for decades. More recently, these collections have been made available to a larger public via the Internet. However, to make accessing them truly useful, the contained images need to be made readable and searchable. One step in that direction is document image binarization, the separation of text foreground from page background. This separation makes the text shown in the document images easier to process by humans and other image processing algorithms alike. While reasonably well working binarization algorithms exist, it is not sufficient to just being able to perform the separation of foreground and background well. This separation also has to be achieved in an efficient manner, in terms of execution time, but also in terms of training data used by machine learning based methods. This is necessary to make binarization not only theoretically possible, but also practically viable.

    In this thesis, we explore different ways to achieve efficient binarization in terms of execution time by improving the implementation and the algorithm of a state-of-the-art binarization method. We find that parameter prediction, as well as mapping the algorithm onto the graphics processing unit (GPU) help to improve its execution performance. Furthermore, we propose a binarization algorithm based on recurrent neural networks and evaluate the choice of its design parameters with respect to their impact on execution time and binarization quality. Here, we identify a trade-off between binarization quality and execution performance based on the algorithm’s footprint size and show that dynamically weighted training loss tends to improve the binarization quality. Lastly, we address the problem of training data efficiency by evaluating the use of interactive machine learning for reducing the required amount of training data for our recurrent neural network based method. We show that user feedback can help to achieve better binarization quality with less training data and that visualized uncertainty helps to guide users to give more relevant feedback.

  • 1743.
    Westphal, Florian
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datalogi och datorsystemteknik.
    Grahn, Håkan
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datalogi och datorsystemteknik.
    Lavesson, Niklas
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datalogi och datorsystemteknik.
    User Feedback and Uncertainty in User Guided Binarization2018Ingår i: International Conference on Data Mining Workshops / [ed] Tong, H; Li, Z; Zhu, F; Yu, J, IEEE Computer Society, 2018, s. 403-410, artikel-id 8637367Konferensbidrag (Refereegranskat)
    Abstract [en]

    In a child’s development, the child’s inherent ability to construct knowledge from new information is as important as explicit instructional guidance. Similarly, mechanisms to produce suitable learning representations, which can be trans- ferred and allow integration of new information are important for artificial learning systems. However, equally important are modes of instructional guidance, which allow the system to learn efficiently. Thus, the challenge for efficient learning is to identify suitable guidance strategies together with suitable learning mechanisms.

    In this paper, we propose guided machine learning as source for suitable guidance strategies, we distinguish be- tween sample selection based and privileged information based strategies and evaluate three sample selection based strategies on a simple transfer learning task. The evaluated strategies are random sample selection, i.e., supervised learning, user based sample selection based on readability, and user based sample selection based on readability and uncertainty. We show that sampling based on readability and uncertainty tends to produce better learning results than the other two strategies. Furthermore, we evaluate the use of the learner’s uncertainty for self directed learning and find that effects similar to the Dunning-Kruger effect prevent this use case. The learning task in this study is document image binarization, i.e., the separation of text foreground from page background and the source domain of the transfer are texts written on paper in Latin characters, while the target domain are texts written on palm leaves in Balinese script.

  • 1744.
    Westphal, Florian
    et al.
    Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik.
    Grahn, Håkan
    Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik.
    Lavesson, Niklas
    Högskolan i Jönköping, Tekniska Högskolan, JTH, Datateknik och informatik, JTH, Jönköping AI Lab (JAIL). Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik.
    User Feedback and Uncertainty in User Guided Binarization2018Ingår i: International Conference on Data Mining Workshops / [ed] H. Tong, Z. Li, F. Zhu, & J. Yu, IEEE Computer Society, 2018, s. 403-410, artikel-id 8637367Konferensbidrag (Refereegranskat)
    Abstract [en]

    In a child’s development, the child’s inherent ability to construct knowledge from new information is as important as explicit instructional guidance. Similarly, mechanisms to produce suitable learning representations, which can be trans- ferred and allow integration of new information are important for artificial learning systems. However, equally important are modes of instructional guidance, which allow the system to learn efficiently. Thus, the challenge for efficient learning is to identify suitable guidance strategies together with suitable learning mechanisms.

    In this paper, we propose guided machine learning as source for suitable guidance strategies, we distinguish be- tween sample selection based and privileged information based strategies and evaluate three sample selection based strategies on a simple transfer learning task. The evaluated strategies are random sample selection, i.e., supervised learning, user based sample selection based on readability, and user based sample selection based on readability and uncertainty. We show that sampling based on readability and uncertainty tends to produce better learning results than the other two strategies. Furthermore, we evaluate the use of the learner’s uncertainty for self directed learning and find that effects similar to the Dunning-Kruger effect prevent this use case. The learning task in this study is document image binarization, i.e., the separation of text foreground from page background and the source domain of the transfer are texts written on paper in Latin characters, while the target domain are texts written on palm leaves in Balinese script.

  • 1745.
    Westphal, Florian
    et al.
    Blekinge Institute of Technology, Karlskrona, Sweden.
    Lavesson, Niklas
    Högskolan i Jönköping, Tekniska Högskolan, JTH, Datateknik och informatik, JTH, Jönköping AI Lab (JAIL). Blekinge Institute of Technology, Karlskrona, Sweden.
    Grahn, Håkan
    Blekinge Institute of Technology, Karlskrona, Sweden.
    A case for guided machine learning2019Ingår i: Machine learning and knowledge extraction: Third IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2019, Canterbury, UK, August 26–29, 2019, Proceedings / [ed] A. Holzinger, P. Kieseberg, A. M. Tjoa & E. Weippl, Cham: Springer, 2019, s. 353-361Konferensbidrag (Refereegranskat)
    Abstract [en]

    Involving humans in the learning process of a machine learning algorithm can have many advantages ranging from establishing trust into a particular model to added personalization capabilities to reducing labeling efforts. While these approaches are commonly summarized under the term interactive machine learning (iML), no unambiguous definition of iML exists to clearly define this area of research. In this position paper, we discuss the shortcomings of current definitions of iML and propose and define the term guided machine learning (gML) as an alternative.

  • 1746.
    Westphal, Florian
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datalogi och datorsystemteknik.
    Lavesson, Niklas
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datalogi och datorsystemteknik.
    Grahn, Håkan
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datalogi och datorsystemteknik.
    Document Image Binarization Using Recurrent Neural Networks2018Ingår i: Proceedings - 13th IAPR International Workshop on Document Analysis Systems, DAS 2018, IEEE, 2018, s. 263-268Konferensbidrag (Refereegranskat)
    Abstract [en]

    In the context of document image analysis, image binarization is an important preprocessing step for other document analysis algorithms, but also relevant on its own by improving the readability of images of historical documents. While historical document image binarization is challenging due to common image degradations, such as bleedthrough, faded ink or stains, achieving good binarization performance in a timely manner is a worthwhile goal to facilitate efficient information extraction from historical documents. In this paper, we propose a recurrent neural network based algorithm using Grid Long Short-Term Memory cells for image binarization, as well as a pseudo F-Measure based weighted loss function. We evaluate the binarization and execution performance of our algorithm for different choices of footprint size, scale factor and loss function. Our experiments show a significant trade-off between binarization time and quality for different footprint sizes. However, we see no statistically significant difference when using different scale factors and only limited differences for different loss functions. Lastly, we compare the binarization performance of our approach with the best performing algorithm in the 2016 handwritten document image binarization contest and show that both algorithms perform equally well.

  • 1747.
    Westphal, Florian
    et al.
    Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik.
    Lavesson, Niklas
    Högskolan i Jönköping, Tekniska Högskolan, JTH, Datateknik och informatik, JTH, Jönköping AI Lab (JAIL). Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik.
    Grahn, Håkan
    Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik.
    Document Image Binarization Using Recurrent Neural Networks2018Ingår i: Proceedings - 13th IAPR International Workshop on Document Analysis Systems, DAS 2018, 2018, s. 263-268Konferensbidrag (Refereegranskat)
    Abstract [en]

    In the context of document image analysis, image binarization is an important preprocessing step for other document analysis algorithms, but also relevant on its own by improving the readability of images of historical documents. While historical document image binarization is challenging due to common image degradations, such as bleedthrough, faded ink or stains, achieving good binarization performance in a timely manner is a worthwhile goal to facilitate efficient information extraction from historical documents. In this paper, we propose a recurrent neural network based algorithm using Grid Long Short-Term Memory cells for image binarization, as well as a pseudo F-Measure based weighted loss function. We evaluate the binarization and execution performance of our algorithm for different choices of footprint size, scale factor and loss function. Our experiments show a significant trade-off between binarization time and quality for different footprint sizes. However, we see no statistically significant difference when using different scale factors and only limited differences for different loss functions. Lastly, we compare the binarization performance of our approach with the best performing algorithm in the 2016 handwritten document image binarization contest and show that both algorithms perform equally well.

  • 1748.
    Wetzer, Elisabeth
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Lindblad, Joakim
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Sintorn, Ida-Maria
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Hultenby, Kjell
    Karolinska Institute.
    Sladoje, Natasa
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Towards automated multiscale imaging and analysis in TEM: Glomeruli detection by fusion of CNN and LBP maps2018Ingår i: Swedish Symposium on Deep Learning, 2018Konferensbidrag (Övrigt vetenskapligt)
  • 1749.
    Wetzer, Elisabeth
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Lindblad, Joakim
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Sintorn, Ida-Maria
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Hultenby, Kjell
    Karolinska Institute.
    Sladoje, Natasa
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Towards automated multiscale imaging and analysis in TEM: Glomerulus detection by fusion of CNN and LBP maps2018Ingår i: Workshop on BioImage Computing @ ECCV 2018, Springer, 2018Konferensbidrag (Refereegranskat)
    Abstract [en]

    Glomerulal structures in kidney tissue have to be analysed at a nanometer scale for several medical diagnoses. They are therefore commonly imaged using Transmission Electron Microscopy. The high resolution produces large amounts of data and requires long acquisition time, which makes automated imaging and glomerulus detection a desired option. This paper presents a deep learning approach for Glomerulus detection, using two architectures, VGG16 (with batch normalization) and ResNet50. To enhance the performance over training based only on intensity images, multiple approaches to fuse the input with texture information encoded in local binary patterns of different scales have been evaluated. The results show a consistent improvement in Glomerulus detection when fusing texture-based trained networks with intensity-based ones at a late classification stage.

  • 1750.
    Wiberg, Viktor
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för fysik.
    Terrain machine learning: A predictive method for estimating terrain model parameters using simulated sensors, vehicle and terrain2018Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Predicting terrain trafficability of deformable terrain is a difficult task with applications in e.g, forestry, agriculture, exploratory missions. The currently used techniques are neither practical, efficient, nor sufficiently accurate and inadequate for certain soil types. An online method which predicts terrain trafficability is of interest for any vehicle with purpose to reduce ground damage, improve steering and increase mobility. This thesis presents a novel approach for predicting the model parameters used in modelling a virtual terrain. The model parameters include particle stiffness, tangential friction, rolling resistance and two parameters related to particle plasticity and adhesion. Using multi-body dynamics, both vehicle and terrain can be simulated, which allows for an efficient exploration of a great variety of terrains. A vehicle with access to certain sensors can frequently gather sensor data providing information regarding vehicle-terrain interaction. The proposed method develops a statistical model which uses the sensor data in predicting the terrain model parameters. However, these parameters are specified at model particle level and do not directly explain bulk properties measurable on a real terrain. Simulations were carried out of a single tracked bogie constrained to move in one direction when traversing flat, homogeneous terrains. The statistical model with best prediction accuracy was ridge regression using polynomial features and interaction terms of second degree. The model proved capable of predicting particle stiffness, tangential friction and particle plasticity, with moderate accuracy. However, it was deduced that the current predictors and training scenarios were insufficient in estimating particle adhesion and rolling resistance. Nevertheless, this thesis indicates that it should be possible to develop a method which successfully predicts terrain model properties.

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