Image Matching by Affine Speed-Up Robust Features

被引：1
|
作者：
Chen, Lin [1 ]
Liu, Jin [1 ]
Cao, Liang [1 ]
机构：
[1] Wuhan Univ, Sch Geodesy & Geomat, Wuhan 430079, Peoples R China
来源：
MIPPR 2011: PATTERN RECOGNITION AND COMPUTER VISION | 2011年 / 8004卷
关键词：
image matching; ASURF; SIFT; SURF;
D O I：
10.1117/12.900333
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
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.
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页数：5
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