Improved fully affine invariant SIFT-based image matching algorithm

HE Bai-gen; ZHU Ming

doi:10.3788/OPE.20111910.2472

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Improved fully affine invariant SIFT-based image matching algorithm

Article | 更新时间：2020-08-12

- Improved fully affine invariant SIFT-based image matching algorithm
- Optics and Precision Engineering Vol. 19, Issue 10, Pages: 2472-2477(2011)
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
  2. 中国科学院研究生院北京,100039
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20111910.2472
  CLC： TP391.4
- Received：24 November 2010，
  
  Revised：15 February 2011，
  
  Published Online：27 October 2011，
  
  Published：25 October 2011
- 稿件说明：
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贺柏根, 朱明. 改进的抗全仿射尺度不变特征变换图像匹配算法[J]. 光学精密工程, 2011,19(10): 2472-2477

HE Bai-gen, ZHU Ming. Improved fully affine invariant SIFT-based image matching algorithm[J]. Editorial Office of Optics and Precision Engineering, 2011,19(10): 2472-2477
贺柏根, 朱明. 改进的抗全仿射尺度不变特征变换图像匹配算法[J]. 光学精密工程, 2011,19(10): 2472-2477 DOI： 10.3788/OPE.20111910.2472.

HE Bai-gen, ZHU Ming. Improved fully affine invariant SIFT-based image matching algorithm[J]. Editorial Office of Optics and Precision Engineering, 2011,19(10): 2472-2477 DOI： 10.3788/OPE.20111910.2472.

摘要

针对现有匹配算法难以解决图像发生仿射变换特别是发生大视角变换时的有效匹配问题

本文对匹配稳定性较好的尺度不变特征变换(SIFT)算法进行了深入研究和改进。借鉴其模拟和归一化相结合的思想对相机光轴的经度角和纬度角进行模拟并采用SIFT算法进行匹配。结果显示

提出的算法不仅保留了SIFT原有的对仿射变换的抵抗能力

而且对视角变换也有很好的鲁棒性

实现了完全的抗仿射变换。实验结果表明

与传统的SIFT算法相比

本文算法对仿射变换尤其是有大视角改变时有更好的适应性。

Abstract

In image matching process

the affine transformation is difficult to avoid. In exiting algorithms

Scale Invarian Feature Transform(SIFT) has strong resistance to changes of scale

rotation

translation and illumination changes generated by affine transformation.However

when an image has a view angle change

especially large change

the SIFT is not satisfactory. This paper researches the principle of the SIFT and improves its matching function.The latitude and longitude of camera axis are simulated firstly

and then the images are matched by using the improved SIFT algorithm. Experiments show that the algorithm not only retains the original advantages of the SIFT algorithm

but also been robust to changes of the angle.It has achieved a complete anti-affine transformation. In conclusions

the proposed algorithm is more suitable to affine transformation

especially large angle changes

as compared with SIFT algorithm.

关键词

Keywords

references

D.G Lowe. Distinctive image features from scale-invariant key points. IJCV, 60(2):91–110, 2004.[2] K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F.Schaffalitzky, T.Kadir, and L. Gool, A comparison of affine region detectors, Int. J. Comput. Vis., 65 (2005),pp.43–72.[3] O. Faugeras, Three-Dimensional Computer Vision: A Geometric Viewpoint, MIT Press, Cambridge, MA, 1993.[4] J.M. Morel and G. Yu. ASIFT: A New Framework for Fully Affine Invariant Image Comparison. to appear in SIAM Journal on Imaging Sciences, 2009.[5] Q. Fan, K. Barnard, A. Amir, A. Efrat, and M. Lin, Matching slides to presentation videos using SIFT and scene background matching, in Proceedings of the 8th ACM International Workshop on Multimedia Information Retrieval, 2006, pp. 239–248.[6] J. Kim, S. Seitz, and M. Agrawala, Video-based document tracking: Unifying your physical and electronic desktops, in Proceedings of the 17th Annual ACM Symposium on User Interface Software and Technology, 2004, pp. 99–107.[7] L. Vacchetti, V. Lepetit, and P. Fua, Stable real-time 3D tracking using online and offline information, IEEE Trans. Pattern Anal. Mach. Intell., 26 (2004), pp. 1385–1391.[8] H. Bay, T. Tuytelaars, and L. Van Gool, Surf: Speeded up robust features, in Computer Vision—ECCV 2006, Springer-Verlag, Berlin, Heidelberg, 2006, pp. 404–417.

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