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

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  • Meng-Hsiun Tsai
  • Yung-Kuan Chan
  • Jiun-Shiang Wang
  • Shu-Wei Guo
  • Jiunn-Lin Wu

Abstract

The techniques of ð ¾ -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.

Suggested Citation

  • Meng-Hsiun Tsai & Yung-Kuan Chan & Jiun-Shiang Wang & Shu-Wei Guo & Jiunn-Lin Wu, 2009. "Color-Texture-Based Image Retrieval System Using Gaussian Markov Random Field Model," Mathematical Problems in Engineering, Hindawi, vol. 2009, pages 1-17, February.
    • Handle: RePEc:hin:jnlmpe:410243
    DOI: 10.1155/2009/410243
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