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Patch Contour Matching by Correlating Fourier Descriptors
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-6096-3648
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-5698-5983
2009 (English)In: Digital Image Computing: Techniques and Applications (DICTA), IEEE Computer Society , 2009, 40-46 p.Conference paper, Published paper (Refereed)
Abstract [en]

Fourier descriptors (FDs) is a classical but still popular method for contour matching. The key idea is to apply the Fourier transform to a periodic representation of the contour, which results in a shape descriptor in the frequency domain. Fourier descriptors have mostly been used to compare object silhouettes and object contours; we instead use this well established machinery to describe local regions to be used in an object recognition framework. We extract local regions using the Maximally Stable Extremal Regions (MSER) detector and represent the external contour by FDs. Many approaches to matching FDs are based on the magnitude of each FD component, thus ignoring the information contained in the phase. Keeping the phase information requires us to take into account the global rotation of the contour and shifting of the contour samples. We show that the sum-of-squared differences of FDs can be computed without explicitly de-rotating the contours. We compare our correlation based matching against affine-invariant Fourier descriptors (AFDs) and demonstrate that our correlation based approach outperforms AFDs on real world data.

Place, publisher, year, edition, pages
IEEE Computer Society , 2009. 40-46 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-51656DOI: 10.1109/DICTA.2009.17ISBN: 978-0-7695-3866-2 (print)OAI: oai:DiVA.org:liu-51656DiVA: diva2:276794
Conference
2009 Digital Image Computing: Techniques and Applications, December 01- 03, Melbourne, Australia
Note
©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Fredrik Larsson, Michael Felsberg and Per-Erik Forssén, Patch Contour Matching by Correlating Fourier Descriptors, 2009, Digital Image Computing: Techniquesand Applications (DICTA), Melbourne, Australia, December 2009. IEEE Computer Society. Available from: 2009-11-12 Created: 2009-11-12 Last updated: 2016-05-04Bibliographically approved
In thesis
1. Methods for Visually Guided Robotic Systems: Matching, Tracking and Servoing
Open this publication in new window or tab >>Methods for Visually Guided Robotic Systems: Matching, Tracking and Servoing
2009 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis deals with three topics; Bayesian tracking, shape matching and visual servoing. These topics are bound together by the goal of visual control of robotic systems. The work leading to this thesis was conducted within two European projects, COSPAL and DIPLECS, both with the stated goal of developing artificial cognitive systems. Thus, the ultimate goal of my research is to contribute to the development of artificial cognitive systems.

The contribution to the field of Bayesian tracking is in the form of a framework called Channel Based Tracking (CBT). CBT has been proven to perform competitively with particle filter based approaches but with the added advantage of not having to specify the observation or system models. CBT uses channel representation and correspondence free learning in order to acquire the observation and system models from unordered sets of observations and states. We demonstrate how this has been used for tracking cars in the presence of clutter and noise.

The shape matching part of this thesis presents a new way to match Fourier Descriptors (FDs). We show that it is possible to take rotation and index shift into account while matching FDs without explicitly de-rotate the contours or neglecting the phase. We also propose to use FDs for matching locally extracted shapes in contrast to the traditional way of using FDs to match the global outline of an object. We have in this context evaluated our matching scheme against the popular Affine Invariant FDs and shown that our method is clearly superior.

In the visual servoing part we present a visual servoing method that is based on an action precedes perception approach. By applying random action with a system, e.g. a robotic arm, it is possible to learn a mapping between action space and percept space. In experiments we show that it is possible to achieve high precision positioning of a robotic arm without knowing beforehand how the robotic arm looks like or how it is controlled.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2009. 93 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1416
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-51657 (URN)LIU-TEK-LIC-2009:24 (Local ID)978-91-7393-527-2 (ISBN)LIU-TEK-LIC-2009:24 (Archive number)LIU-TEK-LIC-2009:24 (OAI)
Presentation
2009-12-18, Glashuset, Hus B, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2009-11-25 Created: 2009-11-12 Last updated: 2016-05-04Bibliographically approved

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Larsson, FredrikFelsberg, MichaelForssén, Per-Erik

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