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基于免疫克隆选择算法的图像分割
引用本文:丛琳, 沙宇恒, 焦李成. 基于免疫克隆选择算法的图像分割[J]. 电子与信息学报, 2006, 28(7): 1169-1173.
作者姓名:丛琳  沙宇恒  焦李成
作者单位:西安电子科技大学智能信息处理研究所,西安,710071;西安电子科技大学智能信息处理研究所,西安,710071;西安电子科技大学智能信息处理研究所,西安,710071
基金项目:国家高技术研究发展计划(863计划);国家高技术研究发展计划(863计划);国家重点基础研究发展计划(973计划)
摘    要:图像分割是图像处理领域中不可缺少的一个分支。该文基于阈值分割方法,将免疫克隆选择优化算法应用到图像分割中,提出了一种新的图像分割算法。详细叙述了算法机理,并对算法复杂度进行了理论分析以及实验数据比较。在仿真实验中,将遗传算法和免疫克隆选择算法分别独立运行10次,对10次得到的阈值以及均值、方差进行了比较,并将函数评价次数作为算法复杂度的评价指标。该文算法不仅能够对图像进行准确的分割,而且在同样的种群规模下能够以较少的迭代代数和较低的函数评价次数得到最优阈值。仿真结果表明,该方法应用在图像分割中是可行的、有效的。

关 键 词:图像分割  人工免疫系统  克隆选择   遗传算法
文章编号:1009-5896(2006)07-1169-05
收稿时间:2004-11-22
修稿时间:2005-07-25

Application of Immune Clone Selection Algorithm to Image Segmentation
Cong Lin, Sha Yu-heng, Jiao Li-cheng. Application of Immune Clone Selection Algorithm to Image Segmentation[J]. Journal of Electronics & Information Technology, 2006, 28(7): 1169-1173.
Authors:Cong Lin  Sha Yu-heng  Jiao Li-cheng
Abstract:Image segmentation is a significant part in image processing field. Inspired by the threshold-based segmentation methods, a novel algorithm based on immune clone selection and optimal entropy theory is presented in this paper. Immune clone selection algorithm performs not only local but also global search, and has better performance than Genetic Algorithm(GA) in searching for the optimal entropy threshold of images. The algorithm is depicted in detail and the computational complexity is given. In experiments, natural image and SAR image are selected, and the algorithm runs ten times independently and the mean numbers of function values are presented as the evaluation of the algorithm complexity. It shows that the algorithm presented in this paper can find better solutions with small generation and mean numbers of function values. So this method has better performance in stabilization and convergence than GA. Experimental results show that this method is feasible and effective.
Keywords:Image segmentation   Artificial immune system   Clone selection   Genetic Algorithm (GA)
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