Empirical investigation of multiple query content-based image retrieval

Multiple query image retrieval system emerged as a promising solution to effectively understand the user interest and communicate it to the system in order to retrieve images relevant to the user query. It consists in providing multiple example images to CBIR system in order to better reflect the information meant by the user. In the literature, multiple query-based retrieval systems have been proposed. In this paper, we investigate experimentally these existing multiple query content-based image retrieval systems and compare them empirically. These approaches are assessed using an image collection from Corel database. We first studied the effect of image query scoring and feature weighting. Then, we compared their performance.