Image segmentation by histogram thresholding using hierarchical cluster analysis

被引：147
|
作者：
Arifin, Agus Zainal
Asano, Akira
机构：
[1] Hiroshima Univ, Grad Sch Engn, Hiroshima 7398527, Japan
[2] Hiroshima Univ, Fac Integrated Arts & Sci, Div Math & Informat Sci, Higashihiroshima 7398521, Japan
来源：
PATTERN RECOGNITION LETTERS | 2006年 / 27卷 / 13期
关键词：
image thresholding; clustering; inter-class variance; intra-class variance;
D O I：
10.1016/j.patrec.2006.02.022
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper proposes a new method of image thresholding by using cluster organization from the histogram of an image. A new similarity measure proposed is based on inter-class variance of the clusters to be merged and the intra-class variance of the new merged cluster. Experiments on practical images illustrate the effectiveness of the new method. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码：1515 / 1521
页数：7
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