@inproceedings{Kopf_2005a,
author={Kopf, S. and Haenselmann, T. and Effelsberg, W.},
booktitle={Multimedia and Expo, 2005. ICME 2005. IEEE International Conference on},
title={Enhancing curvature scale space features for robust shape classification},
year={2005},
month={July},
pages={4 pp.-},
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},
doi={10.1109/ICME.2005.1521464},}