A high-efficiency point extraction and pattern recognition method for localization and decoding dot-distribution coded points

Jiawen Xin; Rui Wang; Junhua Sun

doi:10.1117/12.3007843

18 December 2023 A high-efficiency point extraction and pattern recognition method for localization and decoding dot-distribution coded points

Jiawen Xin, Rui Wang, Junhua Sun

Author Affiliations +

Proceedings Volume 12963, AOPC 2023: Optical Sensing, Imaging, and Display Technology and Applications; and Biomedical Optics; 129631F (2023) https://doi.org/10.1117/12.3007843
Event: Applied Optics and Photonics China 2023 (AOPC2023), 2023, Beijing, China

Abstract

To achieve precise positioning and accurate recognition of dot-distribution encoding points while enhancing efficiency, this study proposes an approach combining improved grayscale centroid and point pattern matching. The algorithm identifies encoded points using multiple constraints and optimizes grayscale centroid via dynamic threshold calculation. It accurately extracts encoded points centers. An advanced clustering method reduces parameter sensitivity and a novel decoding method employs geometric and computer vision principles. Experimental outcomes demonstrate sub-pixel accuracy, robustness to angles, and a 90% correct recognition rate at a 60-degree angle, holding practical significance.

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Jiawen Xin, Rui Wang, and Junhua Sun "A high-efficiency point extraction and pattern recognition method for localization and decoding dot-distribution coded points", Proc. SPIE 12963, AOPC 2023: Optical Sensing, Imaging, and Display Technology and Applications; and Biomedical Optics, 129631F (18 December 2023); https://doi.org/10.1117/12.3007843

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KEYWORDS

Pattern recognition

Detection and tracking algorithms

Tunable filters

Histograms

Matrices

Computer vision technology

Design and modelling

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