Research Of The On-line Detection Method Of Cigarette Packaging Appearance Quality

With the rapid development of cigarette production technology,cigarette welding and packaging speed running at a high speed,the packaging appearance of cigarettes inevitably has defects such as surface abnormalities,edge abnormalities,and wire drawing abnormalities,which have seriously affected product quality and visual effects.At present,the threshold detection method is usually the main method at the production site.This method compares the detection areas and sets the threshold to judge.It is complicated to operate,requires precise positioning of the image,and has poor recognition effects.In this paper,machine vision technology and image processing technology are applied to the cigarette packaging appearance quality detection.Support vector machine(SVM)and BP neural network classification model in machine learning algorithm and convolution neural network model in deep learning technology are used for research and online test.The details are as follows:This paper studies the image acquisition and image preprocessing,introduces the imaging system of the detection equipment,and studies the image preprocessing methods,mainly including image denoising technology,image sharpening enhancement technology,and cigarette image positioning algorithm.Aiming at the detection method of cigarette package appearance,this paper first designs a detection algorithm based on traditional machine learning.This method combines wavelet transform and gray level co-occurrence matrix algorithm to extract the characteristic parameters of cigarette,and then uses support vector machine and BP neural network to classify and recognize the cigarette image.The experimental results show that the recognition accuracy of the two methods is 96.1% and 89.9% respectively.Secondly,this paper proposes an algorithm based on convolution neural network to detect the appearance quality of cigarette packaging.This method designs a network structure with ten hidden layers on the open-source framework tensorflow,and determines the reasonable network parameters and the optimal performance network model through a series of hyperparameter experiments.The experimental results show that the recognition rate of the network model on the experimental data set reaches 98.78%,and the recognition time of an image is 8ms.Convolution neural network method does not need to extract features manually,which avoids the complexity of the traditional method,and innovates the traditional visual detection method.Finally,the paper introduces the structure design of cigarette packaging appearance quality detection system,and the online installation and testing.Before that,this paper analyzes the software and hardware structure of the system,and carries out online test on the detection method.The test results are good.The visual detection system of the appearance quality of the cigarette package meets the production detection requirements.