Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/43817
標題: Color-Texture-Based Image Retrieval System Using Gaussian Markov Random Field Model
作者: Tsai, M.H.
吳俊霖
Chan, Y.K.
Wang, J.S.
Guo, S.W.
Wu, J.L.
蔡孟勳
詹永寬
關鍵字: genetic algorithm
classification
similarity
期刊/報告no:: Mathematical Problems in Engineering.
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.
URI: http://hdl.handle.net/11455/43817
ISSN: 1024-123X
文章連結: http://dx.doi.org/10.1155/2009/410243
Appears in Collections:資訊管理學系

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