Abstrato

Image Retrieval by Using Colour, Texture and Shape Features

Prof. C. S. Gode,Ms. A. N. Ganar

Image retrieval based on color, texture and shape is a wide area of research scope. In this paper we present a framework for combining all the three i.e. color, texture and shape information, and achieve higher retrieval efficiency. The image and its complement are partitioned into non-overlapping tiles of equal size. The features drawn from conditional co-occurrence histograms between the image tiles and corresponding complement tiles, in RGB color space, serve as local descriptors of color, shape and texture. We apply the integration of the above combination, then we cluster based on alike properties. We also create the co-occurrence matrix. Co-occurrence matrix calculate the feature vector for texture. Canny algorithm is use for edge detection to calculate the feature vector for the shape. Invariant moments are then used to record the shape features. The combination of the color, shape and texture features between image and its complement in conjunction with the shape features provide a robust feature set for image retrieval. The experimental results demonstrate the efficacy of the method.