An interactive image retrieval method

Document Type

Conference Proceeding

Publication Date



© 2016 IEEE. In this paper, we propose an interactive image retrieval method based on interactive image segmentation and relevance feedback. For testing the performance of the algorithm, we built an image database by web crawlers, and added a background label to each image by histogram analysis. For image retrieval, an interactive image segmentation scheme based on GrabCut has been applied to get the region of interest (ROI), and then we use an automatic labeling method to get the training samples of relevance feedback, and then incorporate the background labels into the similarity measurement to decrease the influence of clutters. The experimental results show that this method can reduce the influence of image background on image retrieval, and optimize the search results by the feedback of users.

Publication Title

2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings