2006年 第1卷 第1期
《机械工程前沿（英文）》 >> 2006年 第1卷 第1期 doi: 10.1007/s11465-005-0023-6
Application of a Novel Fuzzy Clustering Method Based on Chaos Immune Evolutionary Algorithm for Edge Detection in Image Processing
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摘要
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.
关键词
disturbance amplitude ; disturbance ; diversity ; generation ; processing
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