Region based Image Indexing and Retrieval System

Abstract

Content based image retrieval (CBIR) system is developed for accessing digital images from large image database. To improve the performance of CBIR system, Region based approach for image retrieval system is gaining a considerable attention in research area. Region based image retrieval (RBIR) system focuses on content from regions of images. Although various RBIR techniques have been developed, there are still many problems not satisfactorily solved. In this paper, a effective region based image indexing and retrieval (RBIR) framework is proposed. The proposed approach employs fast and effective statistical region merging (SRM) algorithm to segment images into meaningful regions and each region is then represented using feature vector which describes the color and texture features of region. These feature vectors are used to perform image indexing and retrieval process. Further to improve the retrieval speed and performance, images with similar regions are grouped together. Color moment, HSV color histogram and autocolor correlogram is used to extract color features whereas Gabor function is used to extract texture features from region. Experimental results and performance measurement shows the efficiency and reliability of proposed RBIR system.