Share Email Print
cover

Proceedings Paper

An image segmentation approach based on chaotic ant colony algorithms
Author(s): Zhongliang Pan; Ling Chen
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Image segmentation is to partition an image into meaningful regions. An image segmentation approach based on chaotic ant colony algorithm is presented in this paper. The approach performs the image segmentation by selecting the optimal threshold values, where the multi-threshold values are used. First of all, an entropy function corresponding to an image is defined. The optimal threshold values are obtained by making the entropy function reach the maximal value. Secondly, an approach based on ant colony algorithm is presented for the computation of the optimal thresholds. In order to improve the computation performance of ant colony algorithms, for example, to avoid the algorithm search being trapped in local optimum, we use chaotic approach to find a better solution whenever all the ants have finished the operations. The chaotic approach searching the space around the ant which is the best so far. Besides, the initial solutions are generated by chaotic approach, this improves the quality of initial ants. The experimental results show that the approach proposed in this paper can get the near optimal threshold.

Paper Details

Date Published: 22 January 2008
PDF: 7 pages
Proc. SPIE 6833, Electronic Imaging and Multimedia Technology V, 683318 (22 January 2008); doi: 10.1117/12.756538
Show Author Affiliations
Zhongliang Pan, South China Normal Univ. (China)
Ling Chen, South China Normal Univ. (China)


Published in SPIE Proceedings Vol. 6833:
Electronic Imaging and Multimedia Technology V
Liwei Zhou; Chung-Sheng Li; Minerva M. Yeung, Editor(s)

© SPIE. Terms of Use
Back to Top