Paper
1 August 2023 Multi-source image matching using improved ORB algorithm
Chao Xu, Huamin Yang, Sitong Yan, ZiYun Wang
Author Affiliations +
Proceedings Volume 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023); 1275429 (2023) https://doi.org/10.1117/12.2684204
Event: 2023 3rd International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 2023, Hangzhou, China
Abstract
Image matching is an essential technique in computer vision for many applications (e.g., image understanding). In order to improve the adaptability of previous matching algorithms to multi-source images (i.e., perspective and panoramic images) and increase the matching accuracy, we propose an improve Oriented FAST and Rotated BRIEF (ORB) matching algorithm. We first use the K-Nearest Neighbor (KNN) algorithm to roughly match the feature points extracted from the uniformly partitioned image grids and calculate their matching scores to obtain high scoring matching pairs. Then, we utilize the regional local consistency constraint and affine transformation verification of the Adaptive Local Affine Matching (AdaLAM) method to further refine the matching pairs. Finally, we perform matching experiments on both perspective and panoramic images and show better matching results than most previous matching approaches.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chao Xu, Huamin Yang, Sitong Yan, and ZiYun Wang "Multi-source image matching using improved ORB algorithm", Proc. SPIE 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 1275429 (1 August 2023); https://doi.org/10.1117/12.2684204
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KEYWORDS
Panoramic photography

Feature extraction

Detection and tracking algorithms

Image resolution

Image sensors

Sensors

Visualization

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