Machine vision based for brake shoe steel back size inspection

Hongzhi Hu; Rui Shao; Yuantao Dai; Zhaohong Ren; Fang Guan

doi:10.1117/12.2681329

8 June 2023 Machine vision based for brake shoe steel back size inspection

Hongzhi Hu, Rui Shao, Yuantao Dai, Zhaohong Ren, Fang Guan

Proceedings Volume 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023); 127072R (2023) https://doi.org/10.1117/12.2681329
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 2023, Changsha, China

Abstract

The traditional dimensional measurement of gate tile steel back is still under the status quo of relying on manual work, which is not conducive to industrialization and automated production. In this paper, we rely on machine vision and image feature extraction to achieve contactless measurement of gate tile backs, preprocess the acquired images, binarization operation, edge detection using Canny operator, and finally obtain the product length and width parameters, square hole length and width parameters, central round hole diameter parameters using Hough transform and least squares method. The experimental results show that the method can accurately measure the index parameters of the gate tile steel backing products, and the detection error is within ±2mm. The method reduces the influence of human factors and environmental factors on the inspection of the gate tile steel backing, improves the measurement accuracy and speed of the quality inspection of the gate tile steel backing, and promotes the automation of the production of the gate tile steel backing to a certain extent.

Citation Download Citation

Hongzhi Hu, Rui Shao, Yuantao Dai, Zhaohong Ren, and Fang Guan "Machine vision based for brake shoe steel back size inspection", Proc. SPIE 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 127072R (8 June 2023); https://doi.org/10.1117/12.2681329

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