Combining Novel features for Content Based Image Retrieval

Recent advances in technology have made fabulous amount of multimedia information on the Internet. Content based image retrieval (CBIR) aims at retrieving the similar set of images from the database corresponding to the users query. To do so, a set of features need to be extracted from the images and stored in the database prior to accepting users query. In this paper we introduce a system for interactive image retrieval that combines different approaches to feature based queries. The proposed technique is tested on two types of datasets, first one consisting of different animals and the second dataset consisting of birds, flowers and buildings. The retrieval accuracy is 96.4% and 92.2% for a database size of 530 each.