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Ting Lei

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Proceedings Article | 10 October 2023 Paper

Improved harris corner point algorithm for anti-vibration hammer line clip gap detection

Liqiang Zhong, Ting Lei, Wenjie Wu

Proceedings Volume 12799, 1279913 (2023) https://doi.org/10.1117/12.3006108

KEYWORDS: Detection and tracking algorithms, Corner detection, Image segmentation, Windows, Semantics, Reconstruction algorithms, Feature extraction, Target recognition, Visual inspection, Matrices

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To address the current problems of low accuracy and poor precision of anti-vibration hammer line clip gap detection, the thesis proposes an improved Harris corner point algorithm for anti-vibration hammer line clip gap detection. Firstly, the DeepLabV3+ semantic segmentation algorithm is used to pre-process the anti-vibration hammer images, and the traditional Harris algorithm is used to obtain the pixel-level corner points as the central corner points, which are continuously approximated by the least squares iterative calculation, and finally the sub-pixel-level corner point coordinates are calculated to greatly improve the accuracy of gap detection. Finally, an adaptive thresholding algorithm is used to find the best threshold value for each image, which improves the accuracy of detection. The experimental results show that the average offset of coordinates using the improved Harris corner point detection algorithm is 0.2 pixels, which is 0.6 pixels lower than the average offset of the Harris corner point detection algorithm and greatly improves the detection accuracy. Hariis corner point detection using the adaptive thresholding algorithm can greatly reduce the number of pseudo corner points and improve the accuracy of detection compared to the traditional manual adjustment of the threshold.

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