Abstract
The main purpose of this article is to study the detection of transparent film on the surface of tobacco packs. Tobacco production line needs an industrial robot to remove the transparent film in the process of unpacking. Therefore, after the industrial robot removes the transparent film, it is necessary to use machine vision technology to determine whether there is transparent film residue on the surface of tobacco packaging. In this article, based on the study of the optical features of semitransparent objects, an algorithm for detecting the residue of transparent film in tobacco packs based on surface features is proposed. According to the difference of surface features between tobacco and film, a probability distribution model considering highlights, saturation, and texture density is designed. Because the probability distribution model integrates many features of tobacco and film, it is more reasonable to distinguish the tobacco film regions. In this article, an appropriate foreground box with a trapezoidal mask and image segmentation algorithm GrabCut is used to segment the foreground area of tobacco pack more accurately, and the possible film area is obtained by image differential and morphological processing. Finally, on the basis of comparing the effect of various machine learning algorithms on the image classification of possible film regions, support vector machine based on color features is used to judge the possible film region. Application results of the system show that the method proposed in this article can effectively detect whether there is film residue on the surface of tobacco pack.
Highlights
With the rise of Industry 4.0, smart factory has become a hot term in today’s industry
We propose a visual detection algorithm for tobacco packaging film based on apparent features
The algorithm is designed based on the difference between the optical features of tobacco and film and divides the tobacco and film regions by fusing the three feature probability distribution models of highlight, saturation, and texture density
Summary
With the rise of Industry 4.0, smart factory has become a hot term in today’s industry. More and more traditional manufacturing enterprises are beginning to explore smart factory.[1,2,3] The development of smart factory has become the guarantee of high quality and healthy development of the tobacco industry. Machine vision technology can be used to replace manpower in many processes of tobacco production line, thereby improving the production efficiency and intelligence of the tobacco industry. During the unpacking process of the tobacco packs on the tobacco production line, the film on the surface of the tobacco packs may fail to be removed. This article uses machine vision technology to solve the detection problem and improve the level of enterprise automation
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