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论文类型：期刊论文

发表时间：2015-08-01

发表刊物：Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics

收录刊物：EI、PKU、ISTIC、Scopus

卷号：27

期号：8

页面范围：1389-1398

ISSN号：10039775

摘要：Feature matching is a basic problem in computer vision, and the method based on feature point is the most common one which has important research value. There are many factors which may affect the matching result of the feature points. In this paper, a novel matching method combined texture information and geometric constraints under projective transformation is proposed. First, the newly developed projective invariant "characteristic number" is introduced to compute the geometric descriptors, then histograms of characteristic numbers for each point are built and the Bhattacharyya distance is used to measure the geometric similarities. Finally, the geometric constraints are applied to the descriptors based on local texture information to generate the criteria of points matching. Experiment results show this method can improve the matching accuracy effectively. It also performs well against large viewpoint changes and senses with similar textures. ?, 2015, Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics. All right reserved.