Abstract: In general, Image retrieval is well-known research and development field in information management. An image contains several types of visual features which are difficult to extract and combine manually by humans. These papers introduce some visual features of an image: color, shape and texture. There is several method of extraction of an image features and study or learning algorithms for retrieving image. Various methods have been proposed and investigated. These papers introduce, color histogram which is mostly used because of their efficiency, robustness and insensitivity to small changes in camera viewpoint.A color histogram store image’s overall color composition. So images with many different appearances can have similar color histogram. Colour histogram is constructed by counting the no of pixels of each color of image. Edges are detected in areas of the image where the intensity level fluctuates sharply, the more rapid the intensity changes the stronger the edge. Texture of each sub-block is obtained by using gray level co-occurrence matrix. A one to one matching scheme is used to compare the query and target image.
Keywords: features extraction, histogram, precision.