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Jinglong Yang

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Proceedings Article | 20 October 2023 Paper

Improved AKAZE feature matching algorithm based on grid motion statistics

Hexin Wang, Xiu Ji, Chaoyue Lang, Jinglong Yang

Proceedings Volume 12916, 1291623 (2023) https://doi.org/10.1117/12.3004799

KEYWORDS: Detection and tracking algorithms, Feature extraction, Light sources and illumination, Image registration, Error analysis, Algorithm testing, Target recognition

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Aiming at the problem that AKAZE algorithm has slow feature extraction speed and low accuracy in the feature matching process, this paper proposes to improve AKAZE's feature matching algorithm based on grid statistical motion. Firstly, in the feature extraction stage, the proposed algorithm uses the oFAST algorithm instead of constructing scale space to extract feature points. Then, the M-LDB descriptor is used for feature point description. Finally, the BF algorithm is used to perform coarse matching of features, and the grid motion statistics (GMS) algorithm is added to achieve the purification of matching point pairs and complete the matching. The performance of the proposed algorithm was compared with the AKAZE and ORB algorithms in the experimental fields and grayscale graph groups. The results show that the improved algorithm not only improves the matching speed, which is more than 2 times faster than the AKAZE algorithm, but also maintains a high matching accuracy, which is similar to the AKAZE algorithm.

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