| Peer-Reviewed

Image Registration Method Based on Optimized SURF Algorithm

Received: 17 November 2019    Accepted: 6 December 2019    Published: 18 December 2019
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Abstract

In order to solve the time consuming problem of image registration based on the traditional SURF algorithm, the image registration method based on the optimized SURF algorithm is proposed. Firstly, the image corner points are extracted by the Shi-Tomasi algorithm, then, the SURF algorithm is used to generate the corner point descriptors and the sparse principle algorithm is used to reduce the dimension of the corner point descriptors. Finally, the bidirectional matching algorithm is used to match. Through the experimental data analysis, the image registration method based on the optimized SURF algorithm is nearly the same in image registration accuracy in comparison with the traditional SIFT algorithm, the traditional SURF algorithm and the other four optimized algorithms, but the time consuming of image registration is decreased by 79.09%, 47.74%, 66.25%, 50.79%, 21.43% and 5.13%, respectively, verifying the instantaneity and effectiveness of the algorithm.

Published in American Journal of Optics and Photonics (Volume 7, Issue 4)
DOI 10.11648/j.ajop.20190704.11
Page(s) 63-69
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

SURF Algorithm, Shi-Tomasi Algorithm, Sparse Principle Algorithm, Bidirectional Matching Algorithm, Image Registration

References
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Cite This Article
  • APA Style

    Zhang Sheng, Li Peihua, Liu Yuli, Qian Mingsi, Ji Changgang, et al. (2019). Image Registration Method Based on Optimized SURF Algorithm. American Journal of Optics and Photonics, 7(4), 63-69. https://doi.org/10.11648/j.ajop.20190704.11

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    ACS Style

    Zhang Sheng; Li Peihua; Liu Yuli; Qian Mingsi; Ji Changgang, et al. Image Registration Method Based on Optimized SURF Algorithm. Am. J. Opt. Photonics 2019, 7(4), 63-69. doi: 10.11648/j.ajop.20190704.11

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    AMA Style

    Zhang Sheng, Li Peihua, Liu Yuli, Qian Mingsi, Ji Changgang, et al. Image Registration Method Based on Optimized SURF Algorithm. Am J Opt Photonics. 2019;7(4):63-69. doi: 10.11648/j.ajop.20190704.11

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  • @article{10.11648/j.ajop.20190704.11,
      author = {Zhang Sheng and Li Peihua and Liu Yuli and Qian Mingsi and Ji Changgang and Zhou Meng},
      title = {Image Registration Method Based on Optimized SURF Algorithm},
      journal = {American Journal of Optics and Photonics},
      volume = {7},
      number = {4},
      pages = {63-69},
      doi = {10.11648/j.ajop.20190704.11},
      url = {https://doi.org/10.11648/j.ajop.20190704.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajop.20190704.11},
      abstract = {In order to solve the time consuming problem of image registration based on the traditional SURF algorithm, the image registration method based on the optimized SURF algorithm is proposed. Firstly, the image corner points are extracted by the Shi-Tomasi algorithm, then, the SURF algorithm is used to generate the corner point descriptors and the sparse principle algorithm is used to reduce the dimension of the corner point descriptors. Finally, the bidirectional matching algorithm is used to match. Through the experimental data analysis, the image registration method based on the optimized SURF algorithm is nearly the same in image registration accuracy in comparison with the traditional SIFT algorithm, the traditional SURF algorithm and the other four optimized algorithms, but the time consuming of image registration is decreased by 79.09%, 47.74%, 66.25%, 50.79%, 21.43% and 5.13%, respectively, verifying the instantaneity and effectiveness of the algorithm.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Image Registration Method Based on Optimized SURF Algorithm
    AU  - Zhang Sheng
    AU  - Li Peihua
    AU  - Liu Yuli
    AU  - Qian Mingsi
    AU  - Ji Changgang
    AU  - Zhou Meng
    Y1  - 2019/12/18
    PY  - 2019
    N1  - https://doi.org/10.11648/j.ajop.20190704.11
    DO  - 10.11648/j.ajop.20190704.11
    T2  - American Journal of Optics and Photonics
    JF  - American Journal of Optics and Photonics
    JO  - American Journal of Optics and Photonics
    SP  - 63
    EP  - 69
    PB  - Science Publishing Group
    SN  - 2330-8494
    UR  - https://doi.org/10.11648/j.ajop.20190704.11
    AB  - In order to solve the time consuming problem of image registration based on the traditional SURF algorithm, the image registration method based on the optimized SURF algorithm is proposed. Firstly, the image corner points are extracted by the Shi-Tomasi algorithm, then, the SURF algorithm is used to generate the corner point descriptors and the sparse principle algorithm is used to reduce the dimension of the corner point descriptors. Finally, the bidirectional matching algorithm is used to match. Through the experimental data analysis, the image registration method based on the optimized SURF algorithm is nearly the same in image registration accuracy in comparison with the traditional SIFT algorithm, the traditional SURF algorithm and the other four optimized algorithms, but the time consuming of image registration is decreased by 79.09%, 47.74%, 66.25%, 50.79%, 21.43% and 5.13%, respectively, verifying the instantaneity and effectiveness of the algorithm.
    VL  - 7
    IS  - 4
    ER  - 

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Author Information
  • Avic Huadong Photoelectric Company Limited, Wuhu, China; State Special Display Engineering Laboratory, Wuhu, China; National Special Display Engineering Research Center, Wuhu, China; Anhui Province Key Laboratory for Modern Display Technology, Wuhu, China

  • Avic Huadong Photoelectric Company Limited, Wuhu, China; State Special Display Engineering Laboratory, Wuhu, China; National Special Display Engineering Research Center, Wuhu, China; Anhui Province Key Laboratory for Modern Display Technology, Wuhu, China

  • Avic Huadong Photoelectric Company Limited, Wuhu, China; State Special Display Engineering Laboratory, Wuhu, China; National Special Display Engineering Research Center, Wuhu, China; Anhui Province Key Laboratory for Modern Display Technology, Wuhu, China

  • Avic Huadong Photoelectric Company Limited, Wuhu, China; State Special Display Engineering Laboratory, Wuhu, China; National Special Display Engineering Research Center, Wuhu, China; Anhui Province Key Laboratory for Modern Display Technology, Wuhu, China

  • Avic Huadong Photoelectric Company Limited, Wuhu, China; State Special Display Engineering Laboratory, Wuhu, China; National Special Display Engineering Research Center, Wuhu, China; Anhui Province Key Laboratory for Modern Display Technology, Wuhu, China

  • Avic Huadong Photoelectric Company Limited, Wuhu, China; State Special Display Engineering Laboratory, Wuhu, China; National Special Display Engineering Research Center, Wuhu, China; Anhui Province Key Laboratory for Modern Display Technology, Wuhu, China

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