Image Segmentation Based on Chaos Immune Clone Selection Algorithm

Authors:
Junna Cheng;Guangrong Ji;Chen Feng
Affiliations:
Electronic Department, Information College, Ocean University of China, 238 Hao, Songling Road, Laoshan Area, Qingdao, 266100, China;Electronic Department, Information College, Ocean University of China, 238 Hao, Songling Road, Laoshan Area, Qingdao, 266100, China;Electronic Department, Information College, Ocean University of China, 238 Hao, Songling Road, Laoshan Area, Qingdao, 266100, China
Venue:
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Year:
2009

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Abstract

Image segmentation is a fundamental step in image processing. Otsu's threshold method is a widely used method for image segmentation. In this paper, a novel image segmentation method based on chaos immune clone selection algorithm (CICSA) and Otus's threshold method is presented. By introducing the chaos optimization algorithm into the parallel and distributed search mechanism of immune clone selection algorithm, CICSA takes advantage of global and local search ability. The experimental results demonstrate that the performance of CICSA on application of image segmentation has the characteristic of stability and efficiency.