Cigarette strip defect detection based on Canny edge detection algorithm

Eliminating defects of missing strips and mislabeling is an important task for cigarette enterprises to ensure product quality. There are various shortcomings in the defect detection methods used in the past, and machine vision technology as a new detection means has been widely used in various production processes in the tobacco industry. In order to suppress the noise interference and better detect the edges in the cigarette strip image, this paper designs a set of image acquisition and analysis system for the detection of defects in cigarette boxes based on the Canny edge detection algorithm, which achieves the purpose of counting by matching the contour with the region of interest, and achieves a good effect of defect detection.