Image Registration based on SIFT Features and Adaptive RANSAC Transform

被引：0
|
作者：
Hossein-Nejad, Zahra [1 ]
Nasri, Mehdi [2 ]
机构：
[1] Islamic Azad Univ, Sirjan Branch, Dept Elect Engn, Sirjan, Iran
[2] Islamic Azad Univ, Khomeinishahr Branch, Young Researchers & Elite Club, Khomeinishahr, Iran
来源：
2016 INTERNATIONAL CONFERENCE ON COMMUNICATION AND SIGNAL PROCESSING (ICCSP), VOL. 1 | 2016年
关键词：
Image registration; SIFT features; RANSAC transform;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Scale invariant feature transform (SIFT) is one of the most applicable algorithms used in the image registration problem for extracting and matching of the features. One of the efficient methods in reducing mismatches in this algorithm is the RANdom SAmple Consensus (RANSAC) method. Besides the applicability of RANSAC, its threshold value is fixed, and it is empirically chosen. In this paper, a new method is proposed where the threshold value is calculated based on the variance between the correct matches' and of mismatches classes. Simulation results confirm the superiority of the chosen threshold in different situations in comparison with classic RANSAC algorithms in terms of CMR and FMR.
引用
收藏
页码：1087 / 1091
页数：5
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