Abstract:Retrieval of similar images from large dataset of brain images across patients would help the experts in the decision diagnosis process of diseases. Generally, visual features such as color, shape and texture are used for the retrieval of similar images in Content-Based Image Retrieval (CBIR) process. In this paper, Histogram of Orient Gradients (HOGs) based feature extraction method is used to retrieve similar brain images from large image database. HOG, a shape feature extraction method is proven to be an effective descriptor for object recognition in general. It has been compared with the texture descriptor called Local binary pattern (LBP) and the results show that method outperforms the texture descriptor. The accuracy of the method is tested under different noise levels and intensity non-uniformity.