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An Improved ORB Image Matching Algorithm Based on Compressed Sensing

  • Yijie Wang
  • Songlin GeEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 905)

Abstract

Aiming at the problems such as large amount of computation, high complexity and slow speed in feature extraction of the existing algorithms, this paper presents an improved ORB image matching algorithm based on compressed sensing. Firstly, compressed sensing is used to compress the target image and the matched image, and obtain sparse matrices of wavelet coefficient respectively. Secondly, the ORB algorithm is used to extract the feature points of the image. Finally, the KNN algorithm is used as a matching strategy to perform image matching. Experimental results show that the algorithm realizes fast image matching and guarantees the matching accuracy.

Keywords

Image matching Compressed sensing ORB algorithm KNN 

Notes

Acknowledgement

The work was supported by the National Natural Science Foundation of China (No. 61762037), Science and Technology Project of Jiangxi Provincial Transport Bureau (No. 2016D0037) and Innovation Fund Designated for Graduate Students of Jiangxi Province (No. YC2017-S253).

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.School of Information EngineeringEast China Jiaotong UniversityNanchangChina

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