Multidimensional Markov Stationary Feature for Image Retrival Systems

  • Md. Saiful Islam Department of Computer Science and Engineering, University of Rajshahi, Rajshahi 6205
  • Md. Emdadul Haque Department of Information and Communication Engineering, University of Rajshahi, Rajshahi 6205
  • Md. Ekramul Hamid Department of Computer Science and Engineering, University of Rajshahi, Rajshahi 6205
Keywords: Markov stationary feature, Markov chain, MMSF, Content based image retrieval

Abstract

Markov Stationary Features (MSF) not only considers the distribution of colors like histogram method does, also characterizes the spatial co-occurrence of histogram patterns. However, handling large scale database of images, simple MSF method is not sufficient to discriminate the images. In this paper, we have proposed a robust content based image retrieval algorithm that enhances the discriminating capability of the original MSF. The proposed Multidimensional MSF (MMSF) algorithm extends the MSF by generating multiple co-occurrence matrices with different quantization levels of an image. Publicly available WANG1000 and Corel10800 databases are used to evaluate the performance of the proposed algorithm. The experimental result justifies the effectiveness of the proposed method.

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Abstract
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PDF
635
Published
2016-11-19
How to Cite
Islam, M. S., Haque, M. E., & Hamid, M. E. (2016). Multidimensional Markov Stationary Feature for Image Retrival Systems. Rajshahi University Journal of Science and Engineering, 44, 113-122. https://doi.org/10.3329/rujse.v44i0.30396