Content Based Image Retrieval Using Multi feature fusion Extraction

The development of multimedia system technology in Content based Image Retrieval (CBIR) System is one in every of the outstanding area to retrieve the images from an oversized collection of database. The feature vectors of the query image are compared with feature vectors of the database images to get matching images.It is much observed that anyone algorithm isn't beneficial in extracting all differing kinds of natural images. Thus an intensive analysis of certain color, texture and shape extraction techniques are allotted to spot an efficient CBIR technique that suits for a selected sort of images. The Extraction of an image includes feature description and feature extraction. During this paper, we tend to projected Color Layout Descriptor (CLD), grey Level CoOccurrences Matrix (GLCM), Marker-Controlled Watershed Segmentation feature extraction technique that extract the matching image based on the similarity of Color, Texture and shape within the database. For performance analysis, the image retrieval timing results of the projected technique is calculated and compared with every of the individual feature.