Content based Image Retrieval System with Hybrid Feature Set and Recently Retrieved Image Library

Abstract

Content based image retrieval system is a fast growing research area, where the visual content of a query image is used to search images from large scale image databases. In this proposed an effective system, both the semantically and visually relevant features are used to retrieve the related images. The challenge for the CBIR system is how to efficiently capture the features of the query image for retrieval. In traditional content based retrieval system, the visual content features of the whole query image are used for the retrieval purpose. But in the proposed system, the object wise features of query image are utilized for the effective retrieval. Moreover, an active Recently Retrieved Image Library (RRI Library) is used, which increases the accuracy in each retrieval. An RRI library uses an index system, which maintains the recently retrieved images, and during the retrieval process, the proposed system searches the pertinent images from both the database as well as the RRI library and hence the retrieval precision is gradually increased in each retrieval. The proposed CBIR method is evaluated by querying diverse images and the retrieval efficacy is analyzed by calculating the precision-recall values for the retrieval results.