Image Matching by Affine Speed-Up Robust Features

摘要：

Affine invariant image comparison is always consequential in computer vision. In this paper, affine-SURF (ASURF) is introduced. Through a series of affine transformations and feature extraction, the matching algorithm becomes more robust with the view and scale change. A kd-tree structure is build to store the feature sets and BBF search algorithm is used in feature matching, then duplicates are removed by the conditional of Euclidean distance ratio. Experiments show it has a good result, comparisons with SIFT and SURF is made to prove its performance.

关键词： image matching ASURF SIFT SURF

作者: Lin Chen Jin Liu Liang Cao

作者单位: School of Geodesy and Geomatics, Wuhan University, Wuhan, 430079, China

会议类型: 国际会议

会议名称: 第七届多光谱图象处理与模式识别国际学术会议

会议地点: 桂林

会议语种:英文

页码: 1-5

在线出版日期: 2011-11-01（万方平台首次上网日期，不代表论文的发表时间）