An Improved Algorithm of the Maximum Entropy Image Segmentation

被引:6
|
作者
He, Yan [1 ]
Jie, Liu [1 ]
Yang Dehong [1 ]
Pu, Wang [1 ]
机构
[1] Chongqing Univ Technol, Coll Comp Sci, Chongqing 400054, Peoples R China
来源
2014 Fifth International Conference on Intelligent Systems Design and Engineering Applications (ISDEA) | 2014年
关键词
Image Segmentation; Maximum Entropy; Arithmetic Mean; Binarization;
D O I
10.1109/ISDEA.2014.255
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
For improving the accuracy of the traditional maximum entropy threshold segmentation algorithm, an improved maximum entropy segmentation algorithm is proposed. Firstly, it determines the possible range of an optimal segmentation threshold according to a simple statistical method, so as to reduce the interference of the background and magnify the proportion of the target region. Secondly, in a certain range of threshold, does image segmentation according to an optimal segmentation threshold, which is obtained by using maximum entropy principle. Simulation experiments show that the improved algorithm not only can improve accuracy and noise immunity effectively, but also can better keep the details of the target region in comparison with the traditional maximum entropy threshold segmentation algorithm.
引用
收藏
页码:157 / 160
页数:4
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