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Abstract-In this paper, aiming to overcome the shortcoming of global color histogram which lack of color spatial distribution information, block color moment is used to describe the color feature. In order to extract the texture feature, Canny operator for edge detection is applied firstly, and then the gray level co-occurrence matrix of the edge image is constructed. The results prove that comprehensive of color and texture in image retrieval method overcomes the limitations of using a single, at the same time it improves the retrieval accuracy and speed.

Abstract-We present a method to automatically register images based on feature similarity and image decomposing by multiple wavelet-transform. We use GHM multi-wavelet to decompose the image, then use mean-shift image segmentation algorithm to extract the image feature. We serve the regional features as matching primitives, and put forward an improved image registration method based on invariant descriptor. The experimental results show that the algorithm in reducing computational complexity and enhance the algorithm's robustness can get better effect.

It is worth studying that how to utilize image features so as to achieve the satisfied result of CBIR (content-based image retrieval). To solve this problem, this paper proposes an adaptive image retrieval algorithm based on color feature and texture feature, in which the two kinds of features are combined and the weight coefficients of them are determined with genetic algorithm. Genetic algorithm, starting from solving practical problems, constructs an initial population with the potential solutions of practical problems. In the proposed algorithm, firstly, the initial population consisted with the weight coefficients of texture features (or color ones) is randomly generated; then, selection, crossover, and mutation are operated so that each new generation of population is gradually closed to the optimal solution; finally, the adaptively adjusted weight coefficients are obtained. Experimental results show that when fusing color feature and texture feature in image retrieval, the introduction of genetic algorithm, by which determine the weight coefficients of two kinds of features, makes both the recall ration and precision ratio of retrieval are improved. The proposed algorithm of image retrieval combined with genetic algorithm can automatically set the optimal weights of the image features according to the different image to be retrieved submitted by users, and can basically achieve the ideal suitable weights and output the relative ideal retrieval results.