The aim of this paper is to review the present state of the art in Content-Based Image Retrieval (CBIR), a technique for retrieving images on the basis of automatically-derived features like color, texture and shape. Our findings are based both on a review of the relevant literature and on discussions with researchers in the field. There is need to find a desired image from a collection is shared by many professional groups, including journalists, design engineers and art historians. During the requirements of image users can vary considerably, it can be useful to illustrate image queries into three levels of abstraction first is primitive features such as color or shape, second is logical features such as the identity of objects shown and last is abstract attributes such as the significance of the scenes depicted. While CBIR systems currently operate well only at the lowest of these levels, most users demand higher levels of retrieval.
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