Color-Texture-Based Image Retrieval System Using Gaussian Markov Random Field Model

被引：2

作者：

Tsai, Meng-Hsiun ^{[1
]}

Chan, Yung-Kuan ^{[1
]}

Wang, Jiun-Shiang ^{[2
]}

Guo, Shu-Wei ^{[2
]}

Wu, Jiunn-Lin ^{[2
]}

机构：

[1] Natl Chung Hsing Univ, Dept Management Informat Syst, Taichung 402, Taiwan

[2] Natl Chung Hsing Univ, Dept Comp Sci & Engn, Taichung 402, Taiwan

来源：

MATHEMATICAL PROBLEMS IN ENGINEERING | 2009年 / 2009卷

关键词：

CLASSIFICATION; ALGORITHM;

D O I：

10.1155/2009/410243

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The techniques of K-means algorithm and Gaussian Markov random field model are integrated to provide a Gaussian Markov random field model (GMRFM) feature which can describe the texture information of different pixel colors in an image. Based on this feature, an image retrieval method is also provided to seek the database images most similar to a given query image. In this paper, a genetic-based parameter detector is presented to decide the fittest parameters used by the proposed image retrieval method, as well. The experimental results manifested that the image retrieval method is insensitive to the rotation, translation, distortion, noise, scale, hue, light, and contrast variations, especially distortion, hue, and contrast variations. Copyright (C) 2009 Meng-Hsiun Tsai et al.

引用

页数：17

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