Detecting Rotational Symmetries using Normalized Convolution
2000 (English)In: Proceedings of the 15th International Conference on Pattern Recognition,2000, IEEE , 2000, 496-500 vol.3 p.Conference paper (Refereed)
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.
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-36323DOI: 10.1109/ICPR.2000.903592Local ID: 30981ISBN: 0-7695-0750-6OAI: oai:DiVA.org:liu-36323DiVA: diva2:257171
15th International Conference on Pattern Recognition, 03-07 September 2000, Barcelona, Spain