A Content Based Image Retrieval System using homogeneity Feature extraction from Recency-based Retrieved Image Library

Abstract

Recently, Content Based Image Retrieval (CBIR) plays a significant role in the image processing field. The construction of large datasets has been facilitated by the developments in data storage and image acquisition technologies. In order to manage these datasets in an efficient manner development of suitable information systems are necessary. Based on image content, CBIR extracts images that are relevant to the given query image from large image databases. Images relevant to a given query image are retrieved by the CBIR system utilizing either low level features such as shape, color, texture and homogeneity or high level features such as human perception. Most of the CBIR systems available in the literature extract only concise feature sets that limit the retrieval efficiency. In this paper, additional feature extraction such as homogeneity based feature extraction is used along with color, shape and texture feature extraction to extract the query image from the database images as well as from the RRI library and also to store the retrieved images in the RRI library. The proposed CBIR technique is evaluated by querying different images and the retrieval efficiency is evaluated by determining precision-recall values for the retrieval results.