Application of Self-learning Image Vision Inspection Technology in Cigarette Appearance Inspection
In response to the high error rate in image reporting during the packaging process of cigarette packaging workshops,an improved scheme for cigarette inspection based on a self-learning digital image analysis algorithm is proposed.Use an industrial camera to capture good and defective images of the appearance of the strip packaging.By binarizing the images and introducing self-learning algorithms into the detection algorithm to automatically distinguish image feature points,the computational efficiency is improved.The improved detection system has reduced the difficulty of debugging,improved the convenience of rapid plate replacement on site,effectively improved the detection speed and accuracy of the packaging process in the rolling and packaging workshop,and reduced the error rate of the appearance inspection of the packaging.
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