Machine vision-based algorithm for tooth workpiece pose subpixel detection

Liujie Tao; Zhigang Liu

doi:10.1117/12.3010684

1 December 2023 Machine vision-based algorithm for tooth workpiece pose subpixel detection

Liujie Tao, Zhigang Liu

Proceedings Volume 12940, Third International Conference on Control and Intelligent Robotics (ICCIR 2023); 129402X (2023) https://doi.org/10.1117/12.3010684
Event: Third International Conference on Control and Intelligent Robotics (ICCIR 2023), 2023, Sipsongpanna, China

Abstract

Aiming to address the issue of pose detection of workpieces in automatic assembly processes, this paper presents an algorithm for detecting the pose of metal gear workpieces. The method utilizes an improved homomorphic filtering algorithm to eliminate spot noise from metal workpieces. The complete gear profile is then obtained through the use of the K-means threshold segmentation method and neighborhood tracking method. The center of the gear is determined with the gravity center method, and a virtual circle is scanned with the center as its point of origin. The subpixel feature points of the tooth profile are determined by the least square method, enabling the exact position and pose of the gear workpiece to be obtained. The results of experimentation demonstrate that this method improves detection accuracy by 41.7%, reduces detection error, and has stronger robustness than pixel-level detection algorithms. The proposed method enables the high precision positioning of the position and pose of the gear workpiece and has practical application value.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Liujie Tao and Zhigang Liu "Machine vision-based algorithm for tooth workpiece pose subpixel detection", Proc. SPIE 12940, Third International Conference on Control and Intelligent Robotics (ICCIR 2023), 129402X (1 December 2023); https://doi.org/10.1117/12.3010684

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