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2000
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Detecting Rotational Symmetries Using Normalized Convolution

9 years 11 months ago
Detecting Rotational Symmetries Using Normalized Convolution
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; first extract local orientation from a gray-scale or color image, second apply normalized convolution on the orientation image with rotational symmetry filters as basis functions. These symmetries can serve as feature points at a high ion level for use in hierarchical matching structures for 3D estimation, object recognition, image database retrieval etc.
Björn Johansson, Gösta H. Granlund, Hans
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2000
Where ICPR
Authors Björn Johansson, Gösta H. Granlund, Hans Knutsson
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