Disparity image feature matching algorithm based on AKAZE and adaptive local affine matching

ZHU Daixian; WU Dong; LIU Shulin; LIU Lingzhi

doi:10.5768/JAO202142.0602006

Journal of Applied Optics > 2021 > 42(6): 1048-1055. > DOI: 10.5768/JAO202142.0602006

ZHU Daixian, WU Dong, LIU Shulin, LIU Lingzhi. Disparity image feature matching algorithm based on AKAZE and adaptive local affine matching[J]. Journal of Applied Optics, 2021, 42(6): 1048-1055. DOI: 10.5768/JAO202142.0602006

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Disparity image feature matching algorithm based on AKAZE and adaptive local affine matching

1.
College of Communication and Information Engineering, Xi'an University of Science and Technology, Xi'an 710054, China
2.
College of Electrical and Control Engineering, Xi'an University of Science and Technology, Xi'an 710054, China

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Received Date: May 18, 2021
Revised Date: June 18, 2021
Available Online: October 17, 2021

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Abstract

Abstract

Aiming at the problem that common image feature matching algorithms will produce a large number of mismatched points in the image feature matching stage for images with parallax, a image feature matching algorithm combining accelerated-KAZE (AKAZE) algorithm with adaptive local affine matching was proposed. Firstly, the AKAZE algorithm was used to extract the feature points. Then, the binary descriptor M-LDB was used for description and the brute force matching was performed to generate coarse matching point pairs. Finally, the image-based affine transformation could provide the characteristic of strong geometric constraints, and adopted adaptive local affine matching to complete fine matching. The experimental results show that the algorithm has the effects of uniform extraction of feature points and accurate matching for image matching with rotation change, scale change, and viewing angle change at the same time. The number of correct feature points extracted is increased by average 1.66 times compared with SIFT algorithm, 1.08 times compared with SURF algorithm, 6.92 times compared with ORB algorithm and 1.23 times compared with GMS algorithm, respectively. It can meet the needs of image matching with large disparity.
- accelerated-KAZE,
- adaptive local affine matching,
- feature matching,
- disparity

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References (18)

References

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Disparity image feature matching algorithm based on AKAZE and adaptive local affine matching