免疫进化模糊聚类算法在边缘检测中的应用 |
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引用本文: | 郭子龙,王孙安. 免疫进化模糊聚类算法在边缘检测中的应用[J]. 西安交通大学学报, 2004, 38(3): 274-277,312 |
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作者姓名: | 郭子龙 王孙安 |
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作者单位: | 西安交通大学机械工程学院,710049,西安 |
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基金项目: | 陕西省自然科学基金资助项目 (2 0 0 1x1 7),陕西省机械制造装备重点实验室资助项目 (0 3JF0 6) |
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摘 要: | 针对图像处理中的模糊边缘检测问题,提出一种免疫进化模糊聚类算法.该算法在传统遗传算法全局随机搜索的基础上,借鉴了生物免疫机制中抗体的多样性保持策略,改善了遗传算法的群体多样性,具有更好的全局搜索能力.实验结果表明,该算法不仅具有很强的模糊边缘和微细边缘检测能力,而且可以减弱基于遗传算法的模糊聚类算法在遗传后期的波动现象.
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关 键 词: | 免疫进化算法 模糊聚类算法 边缘检测 |
文章编号: | 0253-987X(2004)03-0274-04 |
Application of a Novel Fuzzy Clustering Method Based on Immune Evolutionary Algorithm for Edge Detection |
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Abstract: | A novel fuzzy clustering method based on immune evolutionary algorithm (IEFCM) was presented to solve fuzzy edge detection problems in image processing. Based on the global stochastic searching method of classic genetic algorithm(GA), and using the diversity preservation strategy of antibodies in biology immunity mechanism, the method greatly improves the colony diversity of GA and has better global searching capability. The experimental results show that the method can not only correctly detect the fuzzy edge and exiguous edge, but also evidently restrain the degenerating phenomenon during the evolutionary process. |
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Keywords: | immune evolutionary algorithm fuzzy clustering algorithm edge detection |
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