Purifying Sets of Matched Features through RANSAC for Image Retrieval
An image is often represented by a set of local invariant features for many computer vision tasks such as object recognition and content-based image retrieval (CBIR), in which correct and reliable feature matching is an essential and challenging issue. Aiming at the problem of the existence of the false matches in CBIR system, we put forward a post-verification method in this paper where RANSAC algorithm is adopted to verify the primary retrieved images on global geometric consensus with the query image so that the false matches are discarded as outliers and only the correct ones are remained as inliers. Experiments show that RANSAC algorithm used in this context can improve the reliability of CBIR systems efficiently.
image matching CBIR RANSAC algorithm local invariant features
Xu Wangming Fang Kangling Liu Xinhai
College of Information Science and Engineering Wuhan University of Science and Technology Wuhan, China
国际会议
长沙
英文
2077-2080
2010-03-13（万方平台首次上网日期，不代表论文的发表时间）