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DOI:
Journal of Software:2001.12(2):212-218

基于模拟退火的最大似然聚类图像分割算法
张引,潘云鹤
(浙江大学 CAD&CG国家重点实验室,浙江 杭州 310027 浙江大学 人工智能研究所,浙江 杭州 310027)
Simulated Annealing based Maximum Likelihood Clustering Algorithm for Image Segmentation
ZHANG Yin,PAN Yun-he
()
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Received:July 29, 1999    Revised:October 28, 1999
> 中文摘要: 图像分割可视为两类模式分类问题.将最大似然聚类方法应用于图像分割,并采用模拟退火技术求解最大似然聚类,解决了用迭代方法求解最大似然聚类只能得到局部最优解的问题.获得的图像分割效果优于迭代方法和著名的Otsu方法,且分类误差小于迭代方法.
Abstract:Image segmentation can be regarded as the problem of two-class pattern classification. How to apply the maximum likelihood clustering algorithm to image segmentation is discussed in this paper. Simulated annealing technology is used to solve the problem of maximum likelihood clustering, which avoids the local optimal solution of iterative method. It shows better image segmentation effect than the famous Otsu algorithm and iterative method with less classification error than iterative method.
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基金项目:国家自然科学基金资助项目(69803009) 国家自然科学基金资助项目(69803009)
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张引,潘云鹤.基于模拟退火的最大似然聚类图像分割算法.软件学报,2001,12(2):212-218

ZHANG Yin,PAN Yun-he.Simulated Annealing based Maximum Likelihood Clustering Algorithm for Image Segmentation.Journal of Software,2001,12(2):212-218