IMAGE THRESHOLDING - SOME NEW TECHNIQUES

被引：50

作者：

PAL, NR

BHANDARI, D

机构：

[1] Machine Intelligence Unit, Indian Statistical Institute, Calcutta, 700035

来源：

SIGNAL PROCESSING | 1993年 / 33卷 / 02期

关键词：

POISSON DISTRIBUTION; IMAGE SEGMENTATION; CONDITIONAL ENTROPY;

D O I：

10.1016/0165-1684(93)90107-L

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Some of the existing threshold selection techniques have been critically reviewed. Two algorithms based on a new conditional entropy measure of a partitioned image have been formulated. The approximate minimum error thresholding algorithm of Kittler and Illingworth has been implemented considering the Poisson distribution for the gray level instead of the commonly used normal distribution. Justification in support of the Poisson distribution has also been given. This method is found to be much better both from the point of view of convergence and segmented output. The proposed methods have been applied on a number of images and are found to produce good results. Objective evaluation of the thresholds has been done using divergence, region uniformity, correlation between original image and the segmented image, and second order entropy.

引用

页码：139 / 158

页数：20

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