ABSTRACT

With the rapid development of technology, the traditional information retrieval techniques based on keywords are not sufficient, content - based image retrieval (CBIR) has been an active research topic.Content Based Image Retrieval (CBIR) technologies provide a method to find images in large databases by using unique descriptors from a trained image. The ability of the system to classify images based on the training set feature extraction is quite challenging. In this paper we propose to extract features on MRI scanned brain images using Discrete cosine transform and down sample the extracted features by alternate pixel sampling. The dataset so created is investigated using WEKA classifier to check the efficacy of various classification algorithms on our dataset. Results are promising and tabulated.