Granular computing, rough entropy and object extraction

被引：126

作者：

Pal, SK

Shankar, BU ^{[1
]}

Mitra, P

机构：

[1] Indian Stat Inst, Machine Intelligence Unit, Kolkata 700108, W Bengal, India

[2] Indian Inst Technol, Dept Comp Sci & Engn, Kanpur 208016, Uttar Pradesh, India

来源：

PATTERN RECOGNITION LETTERS | 2005年 / 26卷 / 16期

关键词：

rough sets; entropy; image segmentation; set approximation; granules;

D O I：

10.1016/j.patrec.2005.05.007

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The problem of image object extraction in the framework of rough sets and granular computing is addressed. A measure called "rough entropy of image" is defined based on the concept of image granules. Its maximization results in minimization of roughness in both object and background regions; thereby determining the threshold of partitioning. Methods of selecting the appropriate granule size and efficient computation of rough entropy are described. (c) 2005 Elsevier B.V. All rights reserved.

引用

页码：2509 / 2517

页数：9

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