摘要
介绍了模糊划分的原理 ,提出用条件概率与条件熵定义模糊划分的熵 ,并基于最大熵原理设计了一种新的灰度直方图阈值选取算法 .比较可见 KSW熵法是本文方法的一个特例 ,本文方法是 KSW熵法在模糊集上的推广 ,对几例真实目标图像的对比分割实验结果表明本文方法性能优越 .
Based upon the maximum fuzzy partition entropy principle, a novel approach for image segmentation was presented. After the concept of fuzzy partition was introduced briefly, a new definition of fuzzy partition entropy was proposed. A threshold selection approach from gray level histogram through maximizing the entropy of fuzzy partition was put forward. It was demonstrated that KSW entropic thresholding method is just a special case of the approach proposed herein. The experiment was conducted on three real object images. The results show that the proposed approach has better performances than some classical threshold selection methods do.
出处
《红外与毫米波学报》
SCIE
EI
CAS
CSCD
北大核心
2000年第3期219-223,共5页
Journal of Infrared and Millimeter Waves
关键词
图像处理
图像分割
模糊划分
熵
image processing, image segmentation, fuzzy partition, entropy.
