%0 Journal Article
%T Simulated Annealing based Maximum Likelihood Clustering Algorithm for Image Segmentation<br>基于模拟退火的最大似然聚类图像分割算法
%A ZHANG Yin
%A PAN Yun-he
%A <br>张引
%A 潘云鹤
%J 软件学报
%D 2001
%I 
%X 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.
%K simulated annealing
%K maximum likelihood clustering
%K image segmentation<br>模拟退火
%K 最大似然聚类
%K 图像分割
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=7222F967D05086F4&yid=14E7EF987E4155E6&vid=59906B3B2830C2C5&iid=0B39A22176CE99FB&sid=D2742EEE6F4DF8FE&eid=AD16A18DBD734D13&journal_id=1000-9825&journal_name=软件学报&referenced_num=10&reference_num=7