Performance Evaluation of Image Retrieval using Co-occurrence Matrix & Texton Co-Occurrence Matrix

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Sunita P. Aware
Laxaman P. Thakare


This paper put forward a new method of co-occurrence matrix to describe image features. This method can express the spatial correlation of textons. During the course of feature extracting, we have quantized the original images into 256 colors and computed color gradient from the RGB vector space, and then calculated the statistical information of textons to describe image features. Image identification experimental results have shown that our proposed method has the discrimination power of color, texture and shape features, the performances are better than that of Grey Level Co-occurrence Matrix (GLCM) and Color Correlograms (CCG).

Keywords: Imaging and image processing co-occrrence matrix, texton matrix


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