With the development of the technology of multimedia and Internet,visual information is used more widely.As a result, effective methods of managing image databases and visual information are needed.As a key technique,content-based image retrieval (CBIR) has become one of the most active research areas in the past few years. This paper discusses the conception and methods of CBIR. Some future research trends are proposed also.We first give an introduction to the state of the art of content-based image analysis and representation of image content,some common techniques for content-based image retrieval, and other related issues.Then we research a retrieval method based on both color feature and texture feature of BMP image.A deformed HSV color model conformed to color cluster feature of human's vision is established.In the space,a suitable cluster algorithm is used to extract main colors, then the original image is converted to main image. Texture statistics are extracted from the Spatial Grey Level Dependency Matrix of each image. In this paper, we using a kind of comprehensive image retrieval which fuses color and texture features by linear weights and discuss the method which the weights are determined.The CBIR method in this paper use not only color feature but also texture .The experiment gives good results.
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