An Improved SIFT Feature Matching Algorithm

被引：6

作者：

Hua, Yuning ^{[1
]}

Lin, Jing ^{[1
]}

Lin, Chao ^{[2
]}

机构：

[1] Shenyangligong Univ, Dept Informat Sci & Engn, Shenyang, Liaoning, Peoples R China

[2] Franklin Elect, Suzhou, Jiangsu, Peoples R China

来源：

2010 8TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2010年

关键词：

SIFT algorithm; image registration; volume normalization; the bilateral matching algorithm;

D O I：

10.1109/WCICA.2010.5554659

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

For the diversity of feature extraction and the complexity of similarity calculation in the feature-based image registration methods, an improved Scale Invariant Feature Transform (SIFT) feature matching algorithm is proposed. First of all, by using the classic SIFT algorithm, the feature points of the images are extracted. By using the gradients normalized method eigenvector descriptor is formed. Then the feature points are matched according to the Euclidean distance ratio. At last, by using the bilateral matching algorithm, the mismatch points are removed. The experiments show that this method is reliable and practicable.

引用

页码：6109 / 6113

页数：5

共 5 条

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