Efficient Content Based Image Retrieval using Novel Soft Computing Techniques

Retrieval of images based on low level visual features such as color, texture and shape have proven to have its own set of limitations under different conditions. As the number and size of image databases grows, accurate and efficient content-based image retrieval systems become increasingly important in business and in the everyday lives of people around the world. In this paper we describe a novel framework for performing content-based image retrieval using soft computing techniques such as Artificial Neural Network and Fuzzy Logic. Given a user specified query image, the system first extracts image features by using wavelet decomposition. These features can be used for training of Multilayer Feed Forward Back-propagation algorithm and these features will be also used as an input to the Fuzzy Inference System. The experimental results reveal that the performance of image retrieval can be surprisingly enhanced. Keywords— CBIR, Soft Computing, Artificial Neural Network Fuzzy Inference System