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標題: Color-Texture-Based Image Retrieval System Using Gaussian Markov Random Field Model
作者: Tsai, M.H.
Chan, Y.K.
Wang, J.S.
Guo, S.W.
Wu, J.L.
關鍵字: genetic algorithm;classification;similarity
Project: Mathematical Problems in Engineering
期刊/報告no:: Mathematical Problems in Engineering.
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.
ISSN: 1024-123X
DOI: 10.1155/2009/410243
Appears in Collections:資訊網路與多媒體研究所

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