An Efficient Content-Based Image Retrieval Using Threefold Technique

Abstract

Managing large amounts of information in the digital world requires an efficient and effective image retrieval system. Content-based image retrieval (CBIR) has garnered tremendous attention and effort over the past few years. Several CBIR systems have been proposed using both onefold and twofold approaches. This paper introduces a new threefold content-based image retrieval system (TfCBIR), which is built on a threefold approach and consists of two modules. As part of its first module, TfCBIR analyzes images to extract color, texture, and shape information. The second module includes three steps. The first step involves comparing the color feature space of all the images with the query image to find the most similar $S$ images. In the next step, the shape feature space is compared with the image query for the $S$ images obtained in the first step to retrieve the closest $S1$ images. Finally, in the third step, the texture feature space is compared with the query image for the $S1$ images found in the second step, and the $R$ most relevant images to the query image are obtained as output. The proposed TfCBIR system has been shown to outperform existing state-of-the-art CBIR methods.