Application of a Novel Fuzzy Clustering Method Based on Chaos Immune Evolutionary Algorithm for Edge Detection in Image Processing |
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Authors: | Wang Sun-an and Guo Zi-long |
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Affiliation: | (1) School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, 710049, China |
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Abstract: | A novel fuzzy clustering method based on chaos immune evolutionary algorithm (CIEFCM) is presented to solve fuzzy edge detection
problems in image processing. In CIEFCM, a tiny disturbance is added to a filial generation group using a chaos variable and
the disturbance amplitude is adjusted step by step, which greatly improves the colony diversity of the immune evolution algorithm
(IEA). The experimental results show that the method not only can correctly detect the fuzzy edge and exiguous edge but can
evidently improve the searching efficiency of fuzzy clustering algorithm based on IEA.
Translated from Journal of Xi’an Jiaotong University, 2004, 38(7) (in Chinese) |
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Keywords: | immune evolutionary algorithm chaos search fuzzy clustering algorithm edge detection |
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