Abstract
It was proposed, in this paper, an algorithm based on machine vision to deal with the problems of low efficiency and large error in profile detection of industrial steel plates. The image filtering operation is used to remove the noise of the steel plate picture, and a method for judging the image filtering effect is proposed. And an image segmentation method combining OTSU and Canny algorithm is designed to achieve dynamic segmentation of steel plate images to obtain the best segmentation effect. In order to fit steel plates with head and tail deformation or camber, a sub-pixel edge fitting method based on cubic B-spline interpolation was proposed to obtain the sub-pixel coordinates of steel plate contour, which provides data basis for crop shearing. The experimental results show that this method has high detection speed and precision and can meet the actual production needs.
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This research work was financially supported by the Youth Science Foundation of Liaoning Province, China.
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Cao, J., Ma, R., Pang, R., Qi, Y. (2021). Sub-pixel Edge Contour Detection Algorithm Based on Cubic B-Spline Interpolation. In: Li, Y., Zhu, Q., Qiao, F., Fan, Z., Chen, Y. (eds) Advances in Simulation and Process Modelling. ISSPM 2020. Advances in Intelligent Systems and Computing, vol 1305. Springer, Singapore. https://doi.org/10.1007/978-981-33-4575-1_4
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DOI: https://doi.org/10.1007/978-981-33-4575-1_4
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