{"title":"基于ZYNQ的卷烟带缺陷检测系统研究","authors":"Shuhang Chen, Ziyang Luo, X. Li, Runhua He","doi":"10.1109/ISPDS56360.2022.9874182","DOIUrl":null,"url":null,"abstract":"At present, most of the tobacco quality inspection links use manual, but due to the speed and detection accuracy is not high enough, often lead to a very long quality inspection links, and mistakenly checked cigarettes into the market will cause economic losses to the company. In order to improve the speed and accuracy of cigarette inspection, a ZYNQ cigarette bar defect detection system was designed and implemented. After binarization processing and image filtering, Sobel operator is used to draw the contour of the image, and then Hough transform is used to get the image of the end face broken line. After rotation correction of the image, the judgment of defect detection is made. If the defect type is determined, the defective products are separated by sound and light alarm and automatic smoke separation device. The experiment shows that the average detection speed of the system for cigarette bar defects is less than 40ms, which meets the real-time requirements of the system. The detection accuracy is 98.67%, and the false detection rate is 0.05%, with low false detection rate.","PeriodicalId":280244,"journal":{"name":"2022 3rd International Conference on Information Science, Parallel and Distributed Systems (ISPDS)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Cigarette strip defect Detection System based on ZYNQ\",\"authors\":\"Shuhang Chen, Ziyang Luo, X. Li, Runhua He\",\"doi\":\"10.1109/ISPDS56360.2022.9874182\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"At present, most of the tobacco quality inspection links use manual, but due to the speed and detection accuracy is not high enough, often lead to a very long quality inspection links, and mistakenly checked cigarettes into the market will cause economic losses to the company. In order to improve the speed and accuracy of cigarette inspection, a ZYNQ cigarette bar defect detection system was designed and implemented. After binarization processing and image filtering, Sobel operator is used to draw the contour of the image, and then Hough transform is used to get the image of the end face broken line. After rotation correction of the image, the judgment of defect detection is made. If the defect type is determined, the defective products are separated by sound and light alarm and automatic smoke separation device. The experiment shows that the average detection speed of the system for cigarette bar defects is less than 40ms, which meets the real-time requirements of the system. The detection accuracy is 98.67%, and the false detection rate is 0.05%, with low false detection rate.\",\"PeriodicalId\":280244,\"journal\":{\"name\":\"2022 3rd International Conference on Information Science, Parallel and Distributed Systems (ISPDS)\",\"volume\":\"118 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 3rd International Conference on Information Science, Parallel and Distributed Systems (ISPDS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPDS56360.2022.9874182\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 3rd International Conference on Information Science, Parallel and Distributed Systems (ISPDS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPDS56360.2022.9874182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Cigarette strip defect Detection System based on ZYNQ
At present, most of the tobacco quality inspection links use manual, but due to the speed and detection accuracy is not high enough, often lead to a very long quality inspection links, and mistakenly checked cigarettes into the market will cause economic losses to the company. In order to improve the speed and accuracy of cigarette inspection, a ZYNQ cigarette bar defect detection system was designed and implemented. After binarization processing and image filtering, Sobel operator is used to draw the contour of the image, and then Hough transform is used to get the image of the end face broken line. After rotation correction of the image, the judgment of defect detection is made. If the defect type is determined, the defective products are separated by sound and light alarm and automatic smoke separation device. The experiment shows that the average detection speed of the system for cigarette bar defects is less than 40ms, which meets the real-time requirements of the system. The detection accuracy is 98.67%, and the false detection rate is 0.05%, with low false detection rate.