Title :
Enhancing curvature scale space features for robust shape classification
Author :
Kopf, Stephan ; Haenselmann, Thomas ; Effelsberg, Wolfgang
Author_Institution :
Dept. of Comput. Sci. IV, Mannheim Univ., Germany
Abstract :
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.
Keywords :
character recognition; code standards; image classification; image enhancement; image representation; image segmentation; video coding; CSS; MPEG-7 standard; automatic character recognition; concave-convex segmentation; curvature scale space feature; image enhancement; shape classification; Cascading style sheets; Character recognition; Computer science; Image recognition; Image segmentation; Kernel; MPEG 7 Standard; Robustness; Shape; Videos;
Conference_Titel :
Multimedia and Expo, 2005. ICME 2005. IEEE International Conference on
Print_ISBN :
0-7803-9331-7
DOI :
10.1109/ICME.2005.1521464