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  • 1601.
    Wahlberg, Fredrik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Mårtensson, Lasse
    Writer identification using the Quill-Curvature feature in old manuscripts2015In: Proceedings of SSBA, 2015, 2015Conference paper (Other academic)
  • 1602.
    Wahlberg, Fredrik
    et al.
    Uppsala universitet, Avdelningen för visuell information och interaktion.
    Brun, Anders
    Uppsala universitet, Avdelningen för visuell information och interaktion.
    Mårtensson, Lasse
    University of Gävle, Faculty of Education and Business Studies, Department of Humanities, Swedish and Gender studies.
    Writer identification using the Quill-Curvature feature in old manuscripts2015In: Proceedings of SSBA, 2015, 2015Conference paper (Other academic)
  • 1603.
    Wahlberg, Fredrik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Dahllöf, Mats
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
    Mårtensson, Lasse
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Scandinavian Languages.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Word Spotting in Pre-Modern Manuscripts using Dynamic Time Warping2012In: Proceedings of SSBA, 2012, 2012Conference paper (Other academic)
  • 1604.
    Wahlberg, Fredrik
    et al.
    Uppsala universitet, Avdelningen för visuell information och interaktion.
    Dahllöf, Mats
    Uppsala universitet, Institutionen för lingvistik och filologi.
    Mårtensson, Lasse
    Uppsala universitet, Institutionen för nordiska språk.
    Brun, Anders
    Uppsala universitet, Avdelningen för visuell information och interaktion.
    Word Spotting in Pre-Modern Manuscripts using Dynamic Time Warping2012In: Proceedings of SSBA, 2012, 2012Conference paper (Other academic)
  • 1605.
    Wahlberg, Fredrik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Mårtensson, Lasse
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Estimating manuscript production dates using both image and language data2016In: Proceedings of SSBA, 2016, 2016Conference paper (Other academic)
  • 1606.
    Wahlberg, Fredrik
    et al.
    Uppsala universitet, Avdelningen för visuell information och interaktion.
    Mårtensson, Lasse
    University of Gävle, Faculty of Education and Business Studies, Department of Humanities, Swedish and Gender studies.
    Brun, Anders
    Uppsala universitet, Avdelningen för visuell information och interaktion.
    Estimating manuscript production dates using both image and language data2016In: Proceedings of SSBA, 2016, 2016Conference paper (Other academic)
  • 1607.
    Wahlberg, Fredrik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Mårtensson, Lasse
    Univ Gavle, Dept Business Studies, Gavle, Sweden.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Large scale continuous dating of medieval scribes using a combined image and language model2016Conference paper (Refereed)
    Abstract [en]

    Finding the production date of a pre-modern manuscript is commonly a long process in historical research, requiring days of work from highly specialised experts. In this paper, we present an automatic dating method based on modelling both the language and the image data. By creating a statistical model over the changes in the pen strokes and short character sequences in the transcribed text, a combination of multiple estimators give a distribution over the time line for each manuscript. We have evaluated our estimation scheme on the medieval charter collection "Svenskt Diplomatariums huvudkartotek" (SDHK), including more than 5300 transcribed charters from the period 1135 - 1509. Our system is capable of achieving a median absolute error of 12 years, where the only human input is a transcription of the charter text. Since reading and transcribing the text is a skill that many researchers and students have, compared to the more specialized skill of dating medieval manuscripts based on palaeographical expertise, we find our novel approach suitable for helping individual researchers to date collections of manuscript pages. For larger collections, transcriptions could also be collected using crowd sourcing.

  • 1608.
    Wahlberg, Fredrik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Mårtensson, Lasse
    Högskolan i Gävle.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Large scale style based dating of medieval manuscripts2015In: Proc. 3rd International Workshop on Historical Document Imaging and Processing, New York: ACM Press, 2015, p. 107-114Conference paper (Refereed)
  • 1609.
    Wahlberg, Fredrik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Wilkinson, Tomas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Historical Manuscript Production Date Estimation using Deep Convolutional Neural Networks2016Conference paper (Refereed)
    Abstract [en]

    Deep learning has thus far not been used for dating of pre-modern handwritten documents. In this paper, we propose ways of using deep convolutional neural networks (CNNs) to estimate production dates for such manuscripts. In our approach, a CNN can either be used directly for estimating the production date or as a feature learning framework for other regression techniques. We explore the feature learning approach using Gaussian Processes regression and Support Vector Regression.The evaluation is performed on a unique large dataset of over 10000 medieval charters from the Swedish collection Svenskt Diplomatariums huvudkartotek (SDHK). We show that deep learning is applicable to the task of dating documents and that the performance is on average comparable to that of a human expert.

  • 1610.
    Walker, Jens
    Umeå University, Faculty of Science and Technology, Department of Physics.
    A motion cueing model for mining and forestry simulator platforms based on Model Predictive Control2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Oryx Simulations produce simulators for mining and forestry machinery used for educational and promotional purposes. The simulators use motion platforms to reflect how the vehicle moves within the simulator. This platform tilts and accelerates the driver in order to enhance the experience. Previously a classical washout filter algorithm has been used to control the platform which leaves something to be desired regarding how well it reflects the vehicles movement, how easy it is to tune and how it handles the limits of the platform.

    This thesis aims to produce a model that accurately reflects angles, velocities and accelerations while in the mean time respecting the limits of the platform. In addition to this the developed model should be easy to modify and tune. This is achieved using so-called Model Predictive Control which achieves the wanted behaviour by predicting how the platform will move based on its current state while implementing the constraints of the platform directly into the model. Since all of the parameters in the model are actual physical quantities, this makes the model easier to tune. A key component in this solution is the so-called tilt coordination which consists of substituting a lateral/longitudinal acceleration with the acceleration of gravity by tilting the driver.

    Constructing and implementing this model in Matlab we verify it by using data extracted from the simulator environment. We see that the parameters consisting of angles, rotational velocities and linear accelerations are tracked very well while respecting the constraints for the platform, constraints that can be easily changed to fit the current simulator.We also see that the model successfully implements tilt coordination into the behaviour of the platform. This model performs extraordinarily well in theory, what remains is to implement this to the motion platform and fine-tune it.

  • 1611.
    Wallenberg, Marcus
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    A Single-Camera Gaze Tracker using Controlled Infrared Illumination2009Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Gaze tracking is the estimation of the point in space a person is “looking at”. This is widely used in both diagnostic and interactive applications, such as visual attention studies and human-computer interaction. The most common commercial solution used to track gaze today uses a combination of infrared illumination and one or more cameras. These commercial solutions are reliable and accurate, but often expensive. The aim of this thesis is to construct a simple single-camera gaze tracker from off-the-shelf components. The method used for gaze tracking is based on infrared illumination and a schematic model of the human eye. Based on images of reflections of specific light sources in the surfaces of the eye the user’s gaze point will be estimated. Evaluation is also performed on both the software and hardware components separately, and on the system as a whole. Accuracy is measured in spatial and angular deviation and the result is an average accuracy of approximately one degree on synthetic data and 0.24 to 1.5 degrees on real images at a range of 600 mm.

  • 1612.
    Wallenberg, Marcus
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Components of Embodied Visual Object Recognition: Object Perception and Learning on a Robotic Platform2013Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Object recognition is a skill we as humans often take for granted. Due to our formidable object learning, recognition and generalisation skills, it is sometimes hard to see the multitude of obstacles that need to be overcome in order to replicate this skill in an artificial system. Object recognition is also one of the classical areas of computer vision, and many ways of approaching the problem have been proposed. Recently, visually capable robots and autonomous vehicles have increased the focus on embodied recognition systems and active visual search. These applications demand that systems can learn and adapt to their surroundings, and arrive at decisions in a reasonable amount of time, while maintaining high object recognition performance. Active visual search also means that mechanisms for attention and gaze control are integral to the object recognition procedure. This thesis describes work done on the components necessary for creating an embodied recognition system, specifically in the areas of decision uncertainty estimation, object segmentation from multiple cues, adaptation of stereo vision to a specific platform and setting, and the implementation of the system itself. Contributions include the evaluation of methods and measures for predicting the potential uncertainty reduction that can be obtained from additional views of an object, allowing for adaptive target observations. Also, in order to separate a specific object from other parts of a scene, it is often necessary to combine multiple cues such as colour and depth in order to obtain satisfactory results. Therefore, a method for combining these using channel coding has been evaluated. Finally, in order to make use of three-dimensional spatial structure in recognition, a novel stereo vision algorithm extension along with a framework for automatic stereo tuning have also been investigated. All of these components have been tested and evaluated on a purpose-built embodied recognition platform known as Eddie the Embodied.

  • 1613.
    Wallenberg, Marcus
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Embodied Visual Object Recognition2017Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Object recognition is a skill we as humans often take for granted. Due to our formidable object learning, recognition and generalisation skills, it is sometimes hard to see the multitude of obstacles that need to be overcome in order to replicate this skill in an artificial system. Object recognition is also one of the classical areas of computer vision, and many ways of approaching the problem have been proposed. Recently, visually capable robots and autonomous vehicles have increased the focus on embodied recognition systems and active visual search. These applications demand that systems can learn and adapt to their surroundings, and arrive at decisions in a reasonable amount of time, while maintaining high object recognition performance. This is especially challenging due to the high dimensionality of image data. In cases where end-to-end learning from pixels to output is needed, mechanisms designed to make inputs tractable are often necessary for less computationally capable embodied systems.Active visual search also means that mechanisms for attention and gaze control are integral to the object recognition procedure. Therefore, the way in which attention mechanisms should be introduced into feature extraction and estimation algorithms must be carefully considered when constructing a recognition system.This thesis describes work done on the components necessary for creating an embodied recognition system, specifically in the areas of decision uncertainty estimation, object segmentation from multiple cues, adaptation of stereo vision to a specific platform and setting, problem-specific feature selection, efficient estimator training and attentional modulation in convolutional neural networks. Contributions include the evaluation of methods and measures for predicting the potential uncertainty reduction that can be obtained from additional views of an object, allowing for adaptive target observations. Also, in order to separate a specific object from other parts of a scene, it is often necessary to combine multiple cues such as colour and depth in order to obtain satisfactory results. Therefore, a method for combining these using channel coding has been evaluated. In order to make use of three-dimensional spatial structure in recognition, a novel stereo vision algorithm extension along with a framework for automatic stereo tuning have also been investigated. Feature selection and efficient discriminant sampling for decision tree-based estimators have also been implemented. Finally, attentional multi-layer modulation of convolutional neural networks for recognition in cluttered scenes has been evaluated. Several of these components have been tested and evaluated on a purpose-built embodied recognition platform known as Eddie the Embodied.

  • 1614.
    Wallenberg, Marcus
    et al.
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Forssen, Per-Erik
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Attentional Masking for Pre-trained Deep Networks2017In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS17), Institute of Electrical and Electronics Engineers (IEEE), 2017Conference paper (Refereed)
    Abstract [en]

    The ability to direct visual attention is a fundamental skill for seeing robots. Attention comes in two flavours: the gaze direction (overt attention) and attention to a specific part of the current field of view (covert attention), of which the latter is the focus of the present study. Specifically, we study the effects of attentional masking within pre-trained deep neural networks for the purpose of handling ambiguous scenes containing multiple objects. We investigate several variants of attentional masking on partially pre-trained deep neural networks and evaluate the effects on classification performance and sensitivity to attention mask errors in multi-object scenes. We find that a combined scheme consisting of multi-level masking and blending provides the best trade-off between classification accuracy and insensitivity to masking errors. This proposed approach is denoted multilayer continuous-valued convolutional feature masking (MC-CFM). For reasonably accurate masks it can suppress the influence of distracting objects and reach comparable classification performance to unmasked recognition in cases without distractors.

  • 1615.
    Wallenberg, Marcus
    et al.
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Forssén, Per-Erik
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Improving Random Forests by Correlation-Enhancing Projections and Sample-Based Sparse Discriminant Selection2016In: Proceedings 13th Conference on Computer and Robot Vision CRV 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 222-227Conference paper (Refereed)
    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.

  • 1616.
    Walter, F.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Synthetic Aperture Radar2000Report (Other scientific)
  • 1617.
    Wang, Chunliang
    Linköping University, Department of Medicine and Health Sciences, Radiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Computer Assisted Coronary CT Angiography Analysis: Disease-centered Software Development2009Licentiate thesis, comprehensive summary (Other academic)
    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.

  • 1618.
    Wang, Chunliang
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Faculty of Health Sciences.
    Computer-­Assisted  Coronary  CT  Angiography  Analysis: From  Software  Development  to  Clinical  Application2011Doctoral thesis, comprehensive summary (Other academic)
    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.

  • 1619.
    Wang, Chunliang
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). KTH Royal Institute Technology, Sweden; Sectra AB, S-58330 Linkoping, Sweden.
    Dahlström, Nils
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Fransson, Sven Göran
    Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences.
    Lundström, Claes
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Smedby, Örjan
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV). KTH Royal Institute Technology, Sweden.
    Real-Time Interactive 3D Tumor Segmentation Using a Fast Level-Set Algorithm2015In: Journal of Medical Imaging and Health Informatics, ISSN 2156-7018, E-ISSN 2156-7026, Vol. 5, no 8, p. 1998-2002Article in journal (Refereed)
    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.

  • 1620.
    Wang, Chunliang
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Sectra, Linkoping, Sweden.
    Forsberg, Daniel
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV). Sectra, Linkoping, Sweden.
    Segmentation of Intervertebral Discs in 3D MRI Data Using Multi-atlas Based Registration2016In: Computational Methods and Clinical Applications for Spine Imaging, CSI 2015, SPRINGER INT PUBLISHING AG , 2016, Vol. 9402, p. 107-116Conference paper (Refereed)
    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%.

  • 1621.
    Wang, Chunliang
    et al.
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Frimmel, Hans
    Institutionen för informationteknologi, Uppsala universitet, Sweden.
    Persson, Anders
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    An interactive software module for visualizing coronary arteries in CT angiography2008In: International Journal of Computer Assisted Radiology and Surgery, ISSN 1861-6410, Vol. 3, no 1-2, p. 11-18Article in journal (Refereed)
    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.

  • 1622.
    Wang, Chunliang
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Smedby, Örjan
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    An Automatic Seeding Method For Coronary Artery Segmentation and Skeletonization in CTA2008Conference paper (Other academic)
    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.

  • 1623.
    Wang, Chunliang
    et al.
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Coronary Artery Segmentation and Skeletonization Based on Competing Fuzzy Connectedness Tree2007In: 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, p. 311-318Conference paper (Refereed)
    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.

  • 1624.
    Wang, Chunliang
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Smedby, Örjan
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Fully automatic brain segmentation using model-guided level set and skeleton based models2013Conference paper (Other academic)
    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.

  • 1625.
    Wang, Chunliang
    et al.
    Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Smedby, Örjan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology in Linköping.
    Integrating automatic and interactive method for coronary artery segmentation: let PACS workstation think ahead2010In: International Journal of Computer Assisted Radiology and Surgery, ISSN 1861-6410, E-ISSN 1861-6429, Vol. 5, no 3, p. 275-285Article in journal (Refereed)
    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.

  • 1626.
    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 Segmentation2015In: Algorithms, ISSN 1999-4893, E-ISSN 1999-4893, Vol. 8, no 2, p. 234-247Article in journal (Refereed)
    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.

  • 1627.
    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 denoising2014In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 102, p. 216-225Article in journal (Refereed)
    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.

  • 1628. Wang, L.
    et al.
    Wang, X.
    Hu, Xiaoming
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
    Distributed tracking and connectivity maintenance with a varying velocity leader2012In: 2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012, IEEE , 2012, p. 1824-1829Conference paper (Refereed)
    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.

  • 1629.
    Wang, Wei
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    Zhai, Qinglin
    Natl Univ Def Technol, Coll Elect Sci & Engn, Changsha 410073, Hunan, Peoples R China..
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
    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 MODEL2017In: 2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), IEEE , 2017, p. 4574-4577Conference paper (Refereed)
    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.

  • 1630.
    Wang Weixing, Bergholm Fredrik
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Froth delineation based on image classification2003In: Minerals engineeringArticle in journal (Other scientific)
  • 1631.
    Wang, Weixing
    et al.
    KTH, School of Information and Communication Technology (ICT). Collage of Physics and Information Engineering, Fuzhou University, Fuzhou, Fujian, China.
    Liang, Y.
    Rock fracture centerline extraction based on hessian matrix and steger algorithm2015In: KSII Transactions on Internet and Information Systems, ISSN 1976-7277, Vol. 9, no 12, p. 5073-5086Article in journal (Refereed)
    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.

  • 1632.
    Wang, Xuerui
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Zhao, Li
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Navigation and Automatic Ground Mapping by Rover Robot2010Independent thesis Advanced level (degree of Master (Two Years)), 30 credits / 45 HE creditsStudent thesis
    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.

  • 1633.
    Wang, Yuquan
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Liu, Hongyi
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Ji, Wei
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Wei
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Realtime collaborating with an industrial manipulator using a constraint-based programming approach2018In: 51st CIRP Conference on Manufacturing Systems, Elsevier, 2018, p. 105-110Conference paper (Refereed)
    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.

  • 1634.
    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 University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    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 Societies2018In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE , 2018, p. 297-304Conference paper (Refereed)
    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.

  • 1635.
    Wedberg, Magnus
    Linköping University, Department of Electrical Engineering, Computer Vision.
    Detecting Rails in Images from a Train-Mounted Thermal Camera Using a Convolutional Neural Network2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    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.

  • 1636.
    Wehrmann, Felix
    Uppsala University, Interfaculty Units, Centre for Image Analysis.
    On Modelling Nonlinear Variation in Discrete Appearances of Objects2004Doctoral thesis, monograph (Other academic)
    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.

  • 1637.
    Wehrmann, Felix
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Bengtsson, Ewert
    Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Modelling non-linearities in images using an auto-associativeneural network2003Conference paper (Refereed)
    Abstract [en]

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

  • 1638.
    Wehrmann, Felix
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Bengtsson, Ewert
    Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Modelling of shapes without landmarks2003Conference paper (Refereed)
    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

  • 1639. Wei, Yangjie
    et al.
    Wu, Chengdong
    Yi, Wang
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Dong, Zaili
    Efficient shape reconstruction of microlens using optical microscopy2015In: IEEE transactions on industrial electronics (1982. Print), ISSN 0278-0046, E-ISSN 1557-9948, Vol. 62, no 12, p. 7655-7664Article in journal (Refereed)
  • 1640. Wei, Yangjie
    et al.
    Wu, Chengdong
    Yi, Wang
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Wang, Wenxue
    Diffusion-based three-dimensional reconstruction of complex surface using monocular vision2015In: Optics Express, ISSN 1094-4087, E-ISSN 1094-4087, Vol. 23, no 23, p. 30364-30378Article in journal (Refereed)
  • 1641.
    Weistrand, Ola
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Mathematics. Interfaculty Units, Centre for Image Analysis. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Mathematics, Mathematics I -V.
    Shape approximation of discrete starshaped objects2006In: Pattern Recognition Letters, Vol. 27, no 16, p. 1934-1941Article in journal (Refereed)
  • 1642.
    Welle, Michael
    et al.
    KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Ericson, Ludvig
    KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Ambrus, Rares
    KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Jensfelt, Patric
    KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    On the use of Unmanned Aerial Vehicles for Autonomous Object Modeling2017In: 2017 European Conference on Mobile Robots, ECMR 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, article id 8098656Conference paper (Refereed)
    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.

  • 1643.
    Wen, Wei
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Communication Systems.
    Khatibi, Siamak
    Blekinge Institute of Technology, Faculty of Computing, Department of Communication Systems.
    Towards Measuring of Depth Perception from Monocular Shadow Technique with Application in a Classical Painting2016In: Journal of Computers, ISSN 1796-203X, Vol. 11, p. 310-319Article in journal (Refereed)
    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.

  • 1644.
    Wen, Wei
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Technology and Aesthetics.
    Siamak, Khatibi
    Blekinge Institute of Technology, Faculty of Computing, Department of Technology and Aesthetics.
    Estimation of Image Sensor Fill Factor Using a Single Arbitrary Image2017In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 17, no 3, p. 620-Article in journal (Refereed)
    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.

  • 1645.
    Wernersson, Björn
    et al.
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Södergren, Mikael
    Linköping University, Department of Electrical Engineering.
    Automatiserad inlärning av detaljer för igenkänning och robotplockning2005Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
    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.

  • 1646.
    Wernersson, Erik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    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 cuts2009In: SSBA Symposium on Image Analysis 2009 / [ed] Josef Bigun and Antanas Verikas, 2009, p. 113-116Conference paper (Other academic)
  • 1647.
    Wernersson, Erik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Luengo Hendriks, Cris L.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Segmentation of Wood Fibres in 3D CT Images Using Graph Cuts2009In: Image Analysis and Processing – ICIAP 2009, Berlin: Springer-Verlag , 2009, p. 92-102Conference paper (Refereed)
    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.

  • 1648.
    Wernersson, Erik L. G.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Luengo Hendriks, Cris L.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Accurate estimation of Gaussian and mean curvature in volumetric images2011In: International Conference on 3D Imaging, Modeling, Processing, Visualization, and Transmission, 3DIMPVT 2011, IEEE Publications , 2011, p. 312-317Conference paper (Refereed)
  • 1649.
    Wernersson, Erik L. G.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Luengo Hendriks, Cris L.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Calculating curvature from orientation fields in volumetric images2011Conference paper (Other academic)
  • 1650.
    Wernersson, Erik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Luengo Hendriks, Cris L.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Generating synthetic μCT images of wood fibre materials2009In: Proc. 6th International Symposium on Image and Signal Processing and Analysis: ISPA 2009, Piscataway, NJ: IEEE , 2009, p. 365-370Conference paper (Refereed)
    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.

30313233343536 1601 - 1650 of 1781
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