A Complex Network-Based Approach for Texture Analysis

被引：0
|
作者：
Backes, Andre Ricardo [1 ]
Casanova, Dalcimar
Bruno, Odemir Martinez
机构：
[1] Univ Fed Uberlandia, Fac Comp, Av Engenheiro Dinz 1178,CP 593, BR-38400 Uberlandia, MG, Brazil
来源：
PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS | 2010年 / 6419卷
基金：
巴西圣保罗研究基金会;
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we propose a novel texture analysis method using the complex network theory. It was investigated how a texture image can be effectively represented, characterized and analyzed in terms of a complex network. The propose uses degree measurements in a dynamic evolution network to compose a set of feasible shape descriptors. Results show that the method is very robust and it presents a very excellent texture discrimination for all considered classes.
引用
收藏
页码：354 / +
页数：2
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