Mathematical Problems in Engineering
Volume 2009 (2009), Article ID 410243, 17 pages
doi:10.1155/2009/410243
Research Article

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

Meng-Hsiun Tsai,1 Yung-Kuan Chan,1 Jiun-Shiang Wang,2 Shu-Wei Guo,2 and Jiunn-Lin Wu2

1Department of Management Information Systems, National Chung Hsing University, 402 Taichung, Taiwan
2Department of Computer Science and Engineering, National Chung Hsing University, 402 Taichung, Taiwan

Received 23 April 2009; Revised 10 August 2009; Accepted 5 November 2009

Academic Editor: Panos Liatsis

Copyright © 2009 Meng-Hsiun Tsai et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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.