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2005 IEEE International Conference on Multimedia and Expo
Enhancing curvature scale space features for robust shape classification
Amsterdam, Netherlands
July 06-July 06
ISBN: 0-7803-9331-7
S. Kopf, Dept. of Comput. Sci. IV, Mannheim Univ., Germany
T. Haenselmann, Dept. of Comput. Sci. IV, Mannheim Univ., Germany
W. Effelsberg, Dept. of Comput. Sci. IV, Mannheim Univ., Germany
The curvature scale space (CSS) technique, which is also part of the MPEG-7 standard, is a robust method to describe complex shapes. The central idea is to analyze the curvature of a shape and derive features from inflection points. A major drawback of the CSS method is its poor representation of convex segments: Convex objects cannot be represented at all due to missing inflection points. We have extended the CSS approach to generate feature points for concave and convex segments of a shape. This generic approach is applicable to arbitrary objects. In the experimental results, we evaluate as a comprehensive example the automatic recognition of characters in images and videos.
Index Terms:
automatic character recognition, curvature scale space feature, CSS, image enhancement, shape classification, MPEG-7 standard, concave-convex segmentation
Citation:
S. Kopf, T. Haenselmann, W. Effelsberg, "Enhancing curvature scale space features for robust shape classification," icme, pp.4 pp., 2005 IEEE International Conference on Multimedia and Expo, 2005
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