Abstract
Sorting the workpiece is one of the key steps in the production practice of workpieces, and machine vision is often used in the sorting process to detect workpiece edge information and screen out other information such as noise. Aiming at the problems of gaussian filtering denoising and artificial threshold setting in traditional Canny edge detection algorithm, an improved Canny algorithm is proposed for edge detection of workpiece. The algorithm uses the MeanShift algorithm instead of Gaussian filtering, which preserves the edge information while denoising. This new algorithm uses the maximum inter-class variance (OSTU) algorithm to obtain the adaptive optimal threshold and improve the adaptability of the algorithm. Experimental results show that under the subjective visual and objective evaluation, the algorithm has significantly improved the edge detection effect of the traditional Canny algorithm.
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