A Comparison of Content Based Image Retrieval Systems

Content-based image retrieval (CBIR) is the application of computer vision techniques to the image retrieval problem. There are two main content-based image retrieval paradigms: one based on visual queries, referred to as query-by-visual-example (QBVE), and the other based on semantic content, denoted as semantic retrieval. In this paper, we compare these two kinds of retrieval systems by conducting experiments on two real typical content-based image retrieval systems: MUVIS and QBSE. The experiments show that QBSE has a better performance than MUVIS, which belongs to QBVE. Semantic space is the most important factor for QBSE system.