Unlike the regular usage, hashing methods, which is ptography, can be used to extract signatures in relation to the detection of similar images. However, finding a hashing function for detecting image similarity seems to be a challenging task, as the hash code needs to represent the content rather than encrypt it. In this paper, a novel content-based image retrieval method based on perceptual image hashing is proposed. The proposed hashing method creates a signature per image based on image rotation and DCT. The acquired hash code is then used to train a memory model to find similar images among a large number of images. In order to evaluate the proposed method, we compare it with some state-of-the-art methods. The results show that our method provides performance faster and better than the leading competitive methods.