Image retrieval using improved texton co-occurrence matrix Online publication date: Thu, 06-Oct-2011
by Anil Balaji Gonde; R.P. Maheshwari; R. Balasubramanian
International Journal of Computational Vision and Robotics (IJCVR), Vol. 2, No. 3, 2011
Abstract: This paper proposed a new technique for content-based image retrieval (CBIR) using a combination of a` trous wavelet transform (AWT) and Julesz's texton elements. AWT is used to decomposse the image into different scales and different texton elements are used to detect the spatial co-relation among the transform coefficients in horizontal, vertical, diagonal and minor diagonal directions which results into texton image. Further co-occurance operations are performed on texton image in horizontal and zigzag direction. Texton co-occurance matrix gives second order statistics related to texton image. The proposed method is tested on natural database (Corel 1000 and Corel 2500) and texture database (Brodatz and USC texture database) and the retrieval results have demonstrated significant improvement in average precision, average recall rate, as well as feature extraction and retrieval time compared to optimal quantised wavelet correlogram (OQWC) and Gabor wavelet correlogram (GWC).
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