Open AccessMultidimensional Markov Stationary Feature for Image Retrival Systems
Author(s) -
Md. Saiful Islam,
Md. Emdadul Haque,
Md. Ekramul Hamid
Publication year - 2016
Publication title -
rajshahi university journal of science and engineering
Language(s) - English
Resource type - Journals
eISSN - 2408-8803
pISSN - 2309-0952
DOI - 10.3329/rujse.v44i0.30396
Subject(s) - histogram , pattern recognition (psychology) , artificial intelligence , computer science , markov chain , feature (linguistics) , image (mathematics) , histogram matching , quantization (signal processing) , data mining , algorithm , machine learning , linguistics , philosophy
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.