Threshold selection using Renyi's entropy

被引：296
|
作者：
Sahoo, P
Wilkins, C
Yeager, J
机构：
[1] Department of Mathematics, University of Louisville, Louisville
来源：
PATTERN RECOGNITION | 1997年 / 30卷 / 01期
关键词：
Renyi entropy; Shannon entropy; image thresholding; maximum entropy sum method; entropic correlation method;
D O I：
10.1016/S0031-3203(96)00065-9
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Image segmentation is an important and fundamental task in many digital image processing systems. Image segmentation by thresholding is the simplest technique and involves the basic assumption that objects and background in the digital image have distinct gray-level distributions. In this paper, we present a general technique for thresholding of digital images based on Renyi's entropy. Our method includes two of the previously proposed well known global thresholding methods. The effectiveness of the proposed method is demonstrated by using examples from the real-world and synthetic images.
引用
收藏
页码：71 / 84
页数：14
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