The CBIR will in general search, retrieve and index an image. The positioning of a CBIR framework relies upon the impossible to miss image representation, design, highlights and so on. CBIR keeps away from numerous issues related to conventional strategies for recovering images by utilizing keywords. The explanation of a CBIR framework mainly depends on the specific image portrayal and coordinating closeness capacities utilized [1]. Content-Based Image Retrieval framework depends on the recovery of the indistinguishable pictures from the wide database when a query picture is a feed as a contribution to the framework. The entire working of Content-Based Image Retrieval (CBIR) framework is to give comparable matches of a question contribution from enormous and various datasets. Profitable sanctioning of a CBIR framework requires arrangement, characterization, ordering, and repossession of images.

Keywords: CBIR; retrieval; feature extraction; classifier; Back Propagation Neural Network (BPNN)