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Stereo vision algorithms in reconfigurable hardware for robotics applications
Mälardalen University, School of Innovation, Design and Engineering. (Robotik)
2011 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis presents image processing solutions in FPGA based embedded vision systems. Image processing is a demanding process but the information that can be extracted from images is very useful and can be used for many tasks like mapping and navigation, object detection and recognition, collision detection and more.

Image processing or analysis involves reading images from a camera system, improve an image with respect to colour fidelity and white balance, removing distortion, extracting salient information. The mentioned steps are often referred to as low to medium level image processing and involve large amounts of data and fairly simple algorithms suitable for parallel processing.

Medium to high level processing involves a reduced amount of data and more complex algorithms. Object recognition which involves matching image features to information stored in a database is of higher complexity.

A vision system can be used in anything from a car to industry processes to mobile robots playing soccer or assisting people in their homes. A vision system often works with video streams that are processed to find pieces that can be handled in an industry process, detect obstacles that may be potential hazards in traffic or to find and track landmarks in the environment that can be used to build and navigate from. This involves large amount of calculations and this is a problem, even though modern computers are fast they may still not be able to execute the desired algorithms with the frequency wanted. Even if there are computers that are fast enough they are bulky and require a lot of power. They are not suitable for incorporating on small mobile robots.

In this thesis I will present the image processing sequence to give an understanding of the complexity of the processes involved and I will discuss some processing platforms suitable for image processing. I will also present my work that is focused on image algorithm implementations for reconfigurable hardware suitable for mobile robots with requirements on speed an power consumption.

Place, publisher, year, edition, pages
Västerås: Mälardalen University , 2011.
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 141
National Category
Computer Science
Research subject
Computer Science
URN: urn:nbn:se:mdh:diva-12977ISBN: 978-91-7485-033-8OAI: diva2:439516
2011-09-26, Lambda, 09:15 (English)
Available from: 2011-09-08 Created: 2011-09-08 Last updated: 2011-09-26Bibliographically approved
List of papers
1. Validation of Stereo Matching for Robot Navigation
Open this publication in new window or tab >>Validation of Stereo Matching for Robot Navigation
2009 (English)In: 14th IEEE International Conference on emerging Technologies and Factory Automation ETFA 2009, 2009Conference paper (Refereed)
Abstract [en]

In this paper a new method is presented for evaluat- ing visual stereo matching. Features are extracted and stereo paired according to their vertical positions in the image, with constraints on the horizontal position, leaving only sane, possible pairs. From feature pairs landmarks are constructed. The landmarks are evaluated using mo- tion estimation from a complementary relative naviga- tion system like odometry, only landmarks calculated from correctly paired features should survive the motion, thus transferring the problem into three dimensional space.

National Category
Engineering and Technology
urn:nbn:se:mdh:diva-9055 (URN)10.1109/ETFA.2009.5347105 (DOI)2-s2.0-77949884708 (ScopusID)9781424427284 (ISBN)
2009 IEEE Conference on Emerging Technologies and Factory Automation, ETFA 2009; Mallorca; Spain; 22 September 2009 through 26 September 2009
Available from: 2010-03-03 Created: 2010-03-03 Last updated: 2013-12-19Bibliographically approved
2. Two Camera System for Robot Applications; Navigation
Open this publication in new window or tab >>Two Camera System for Robot Applications; Navigation
2008 (English)In: 13th IEEE International Conference on Emerging Technologies and Factory Automation, 2008. (ETFA 2008), 2008, 345-352 p.Conference paper (Refereed)
Abstract [en]

Current approaches to feature detection and matching

in images strive to increase the repeatability of the detector

and minimize the degree of outliers in the matching.

In this paper we present a conflicting approach; we suggest

that a lower performance feature detector can produce

a result more than adequate for robot navigation irrespectively

of the amount of outliers. By using an FPGA

together with two cameras we can remove the need for

descriptors by performing what we call spurious matching

and the use of 3D landmarks. The approach bypasses

the problem of outliers and reduces the time consuming

task of data association, which slows many matching algorithms.

National Category
Engineering and Technology
urn:nbn:se:mdh:diva-7254 (URN)10.1109/ETFA.2008.4638417 (DOI)2-s2.0-56349088961 (ScopusID)1424415063 (ISBN)
13th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2008; Hamburg; Germany; 15 September 2008 through 18 September 2008
Available from: 2009-09-25 Created: 2009-09-25 Last updated: 2014-01-10Bibliographically approved

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