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Detecting Rotational Symmetries using Normalized Convolution
Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Computer Vision.
Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Computer Vision.ORCID iD: 0000-0002-9091-4724
Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Computer Vision.
2000 (English)In: Proceedings of the 15th International Conference on Pattern Recognition,2000, IEEE , 2000, 496-500 vol.3 p.Conference paper, Published paper (Refereed)
Abstract [en]

Perceptual experiments indicate that corners and curvature are very important features in the process of recognition. This paper presents a new method to detect rotational symmetries, which describes complex curvature such as corners, circles, star, and spiral patterns. It works in two steps: 1) it extracts local orientation from a gray-scale or color image; and 2) it applies normalized convolution on the orientation image with rotational symmetry filters as basis functions. These symmetries can serve as feature points at a high abstraction level for use in hierarchical matching structures for 3D estimation, object recognition, image database retrieval, etc

Place, publisher, year, edition, pages
IEEE , 2000. 496-500 vol.3 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-36323DOI: 10.1109/ICPR.2000.903592Local ID: 30981ISBN: 0-7695-0750-6 (print)OAI: oai:DiVA.org:liu-36323DiVA: diva2:257171
Conference
15th International Conference on Pattern Recognition, 03-07 September 2000, Barcelona, Spain
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2015-01-09

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Johansson, BjörnKnutsson, HansGranlund, Gösta

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