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Proceedings Paper

Threshold segmentation using cultural algorithms for image analysis
Author(s): Zhongliang Pan; Ling Chen; Guangzhao Zhang
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Paper Abstract

The image segmentation is often an important step in the analysis of images. In this paper, an image segmentation method based on cultural algorithms is presented. The method performs the image segmentation by selecting the optimal threshold values. 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 algorithm based on the principle of cultural algorithms is presented for the computation of the optimal thresholds. The algorithm consists of three major components: a population space, a belief space, and a communication protocol that describes how knowledge is exchanged between the first two components. The designs and implementations of the three components are given in detail. The experimental results show that the segmentation method proposed in this paper can obtain the near optimal threshold for image segmentation.

Paper Details

Date Published: 19 February 2008
PDF: 8 pages
Proc. SPIE 6625, International Symposium on Photoelectronic Detection and Imaging 2007: Related Technologies and Applications, 662512 (19 February 2008); doi: 10.1117/12.791025
Show Author Affiliations
Zhongliang Pan, South China Normal Univ. (China)
Ling Chen, South China Normal Univ. (China)
Guangzhao Zhang, Sun Yat-sen Univ. (China)


Published in SPIE Proceedings Vol. 6625:
International Symposium on Photoelectronic Detection and Imaging 2007: Related Technologies and Applications

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