文献类型：期刊文献

英文题名：Image matching based on orientation-magnitude histograms and global consistency

作者：Liang, Jianning[1,2];Liao, Zhenmei[2];Yang, Su[2];Wang, Yuanyuan[3]

机构：[1]E China Univ Sci & Technol, Dept Comp Sci & Engn, Shanghai 200237, Peoples R China;[2]Fudan Univ, Sch Comp Sci & Technol, Shanghai 201203, Peoples R China;[3]Fudan Univ, Dept Elect Engn, Shanghai 200433, Peoples R China

年份：2012

卷号：45

期号：10

起止页码：3825

外文期刊名：PATTERN RECOGNITION

收录：;EI(收录号：20122315100320);WOS:【SCI-EXPANDED(收录号:WOS:000305845300021)】；

基金：Thank the reviewers for improving the quality of the paper. This work is supported by 973 Program (grant No. 2010CB731401), NSFC (grant No. 61071133), Major Program of NSFC (grant No. 91024011), Ministry of Industry and Information Technology of China (grant No. 2010ZX01042-002-003-004), and Science and Technology Commission of Shanghai Municipality (grant No. 09JC1401500).

语种：英文

外文关键词：Image matching; Orientation-magnitude histogram; Global consistency; Steepest descent method

摘要：A novel image matching method based on the gradient space is proposed. Image pyramid combined with the Hessian matrix is used to detect scale-invariant interesting points. A new descriptor i.e. an orientation-magnitude histogram is introduced to describe the image content around an interesting point. The proposed local descriptor is proved to be invariant to image rotation. Since the matching result based on the similarities of the descriptors of interesting points always contains outliers, a steepest descent method that optimizes the global consistency of interesting points is presented to remove false matches. The experiments show that the proposed approach is invariant to rotation and scale, robust to the variation of focal lengths, illumination change, occlusion, noises and image blur. Our approach shows better performance than SIFT on multi-view and affine-transformation images. The application of the proposed method to image registration exhibits a good result. (C) 2012 Elsevier Ltd. All rights reserved.