MINIMUM CROSS ENTROPY THRESHOLDING

被引：602

作者：

LI, CH ^{[1
]}

LEE, CK ^{[1
]}

机构：

[1] HONG KONG POLYTECH,DEPT ELECTR ENGN,HONG KONG,HONG KONG

来源：

PATTERN RECOGNITION | 1993年 / 26卷 / 04期

关键词：

THRESHOLDING; IMAGE SEGMENTATION; MINIMUM CROSS ENTROPY; MAXIMUM ENTROPY METHOD;

D O I：

10.1016/0031-3203(93)90115-D

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The threshold selection problem is solved by minimizing the cross entropy between the image and its segmented version. The cross entropy is formulated in a pixel-to-pixel basis between the two images and a computationally attractive algorithm employing the histogram is developed. Without making a priori assumptions about the population distribution, this method provides an unbiased estimate of a binarized version of the image in an information theoretic sense.

引用

页码：617 / 625

页数：9

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