A new algorithm meant for content based image retrieval (CBIR) is presented in this paper. First the RGB (red, green, and blue) image is converted into HSV (hue, saturation, and value) image, then the H and S images are used for histogram calculation by quantizing into Q levels and the local region of V (value) image is represented by local binary patterns (LBP), which are evaluated by taking into consideration of local difference between the center pixel and its neighbors. LBP extracts the information based on distribution of edges in an image. Two experiments have been carried out for proving the worth of our algorithm. It is further mentioned that the database considered for experiments are Corel 1000 database (DB1), and MIT VisTex database (DB2). The results after being investigated show a significant improvement in terms of their evaluation measures as compared to LBP on RGB spaces separately and other existing techniques.