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

Author:

Tsai Meng-Hsiun1,Chan Yung-Kuan1ORCID,Wang Jiun-Shiang2,Guo Shu-Wei2,Wu Jiunn-Lin2ORCID

Affiliation:

1. Department of Management Information Systems, National Chung Hsing University, 402 Taichung, Taiwan

2. Department of Computer Science and Engineering, National Chung Hsing University, 402 Taichung, Taiwan

Abstract

The techniques of -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.

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Improved color texture descriptors for remote sensing image retrieval;Journal of Applied Remote Sensing;2014-07-24

2. Linear Chromatic Adaptation Transform Based on Delaunay Triangulation;Mathematical Problems in Engineering;2014

3. Audio-Visual-Based Query by Example Video Retrieval;Mathematical Problems in Engineering;2013

4. Domain-Oriented Subject Aware Model for Multimedia Data Retrieval;Mathematical Problems in Engineering;2013

5. Content-based image retrieval by integrating color and texture features;Multimedia Tools and Applications;2012-04-03

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