Laser & Optoelectronics Progress, Volume. 61, Issue 8, 0800003(2024)
Progress in Research on Tobacco Online Inspection Technology Based on Machine Vision
[2] Cheng S, Yang H G, Xu X Q et al. Improved lightweight X-ray aluminum alloy weld defects detection algorithm based on YOLOv5[J]. Chinese Journal of Lasers, 49, 2104005(2022).
[3] Huang X Y, Zhao G R, Huang J et al. Optimization of technological parameters of threshing and redrying based on decision tree and orthogonal experimental design[J]. Tianjin Agricultural Sciences, 26, 69-72(2020).
[4] Luo H Y, Fang W Q, Yang L B et al. Relationship between stem content in lamina and tobacco breakage[J]. Tobacco Science & Technology, 38, 11-13(2005).
[5] Li C G, Sun M, Liu Q et al. Evaluation of practicality of pneumatic cut lamina separation[J]. Tobacco Science & Technology, 43, 5-7(2010).
[6] Li X, Xiong A Y. Application of in site pneumatic sliver classifier FX6[J]. Tobacco Science & Technology, 39, 9-11(2006).
[7] Chen F. Application of HELIUS laser impurity removal in foreign body removal of silk production line[J]. Industrial Design, 152-153(2016).
[8] Ma Y, Yang B F, Hang J J. Design of tobacco strip sorting system incorporating multispectral technology and vertical pneumatic separation[J]. Tobacco Science & Technology, 48, 76-81(2015).
[9] Gao X, Zhang C, Chen J et al. Study on impurity removal effect of AEROSORT[J]. Food Science and Technology and Economy, 43, 104-108(2018).
[10] Zhu S H. Tobacco foreign matter removing devices[P].
[12] Zhang F, Jiang J S, Liu Z C et al. A tobacco foreign object removal device and its removal method using near-infrared spectroscopy technology[P].
[13] Dong Z. Design and research of visual inspection system for tobacco conveying state[D](2022).
[14] Cao J C, Zhou J Q. Cigarette counting recognition based on mathematical morphology[J]. Computer Aided Engineering, 15, 6-10(2006).
[15] Wu X F. Research on cigarette online detection system based on machine vision[D](2011).
[16] Lu F. Research on detection technology of the packaging machines loose ends based on machine vision[J]. Light Industry Machinery, 28, 65-67, 71(2010).
[17] Zhang J. Recognition and counting of color cigarette images based on cluster analysis[D](2007).
[18] Tian X X. Research on segmentation and counting of cigarette images based on genetic algorithm[D](2007).
[19] Sheng F, Song S Y, Xia S P. A real-time cigarettes counting and loose ends detection algorithm[C], 11-15(2016).
[20] Qu H J, Zhang P J, Zhang K, Fei M R, Ma S W, Li X et al. Research on cigarette filter rod counting system based on machine vision[M]. Advanced computational methods in life system modeling and simulation, 761, 513-523(2017).
[21] Xiao Z Y. Research and implementation of cigarette defect detection algorithm[D](2018).
[22] Li J, Lu H H, Wang X et al. Online inspection system for cigarette tipping quality based on machine vision. Tobacco Science and Technology, 52, 109-114(2019).
[23] Ying W, Hu X J, Zhao L. Detection of cigarette missing in packing based on deep convolutional neural network[C], 1252-1256(2017).
[24] Liu H Y, Yuan G W, Yang L et al. An appearance defect detection method for cigarettes based on C-CenterNet[J]. Electronics, 11, 2182(2022).
[25] Yu K P, Wang R, Sun J et al. Image information acquisition device for cigarette visual detection[P].
[26] Wang Z D. A visual inspection system for cigarette appearance defects[P].
[27] Tao X. Application of machine vision in cigarette package detection[D](2007).
[28] Liu H, He F Q, Li R L et al. On-line detection technology of label paper surface defects of small cigarette packs based on machine vision[J]. Acta Tabacaria Sinica, 26, 54-59(2020).
[29] Chen T Y, Chen Y, Fan J W. Improved YOLOv3 algorithm for cigarette case defect detection[J]. Internet of Things Technologies, 11, 51-52, 55(2021).
[30] Xu Z J, Guo S X, Li Y F, Sun X, Zhang X, Xia Z et al. Cigarette packaging quality inspection based on convolutional neural network[M]. Adaptive intelligence and security, 13338, 614-626(2022).
[31] Wang Y S. From defect detection to quality control—visual inspection scheme for printing quality defects of medicine pack/color box[J]. Printing Technology, 70-71(2013).
[32] Chen J. A cigarette box appearance inspection equipment[P].
[33] Zhang Y M. Intelligent cigarette bag appearance inspection equipment[P].
[34] Hu X F, Zhu L J, Lü X M et al. A cigarette box appearance defect detection system[P].
[35] Lu J. Research on GD small pack cigarette detection system based on machine vision and photoelectric technology[D](2021).
[36] Li Y X. Research and simulation of tobacco foreign body image detection technology[D](2018).
[37] Shen W C. Research on tobacco foreign body recognition algorithm based on color model[D](2018).
[38] Zhou S F. Research on tobacco maturity detection technology based on image processing[D](2013).
[39] Hu L. Research on automatic detection technology of cigarette defects based on machine vision[D](2016).
[40] Cao C K. Research on surface quality detection based on image processing[D](2022).
[41] Kittler J. On the accuracy of the Sobel edge detector[J]. Image and Vision Computing, 1, 37-42(1983).
[42] Torre V, Poggio T A. On edge detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 8, 147-163(1986).
[43] Canny J. A computational approach to edge detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 8, 679-698(1986).
[44] Zhuang Z Z. Research on automatic tobacco grading method based on machine vision[D](2016).
[45] Harris C, Stephens M. A combined corner and edge detector[C], 147-151(1988).
[46] Shi J. Good feature to track[C], 593-600(1994).
[47] Liu Y L, Gui Z G. Adaptive image enhancement algorithm with variable weighted matching based on morphology[J]. Journal of Electronics & Information Technology, 36, 1285-1291(2014).
[48] Zhu X L, Chen M, Li X Y et al. A color image edge detection model with morphological amoebas and two kinds of color spaces[J]. Journal of Computer-Aided Design & Computer Graphics, 26, 1060-1066(2014).
[49] Chen M, Zhu X L, Li X Y et al. Improved color image edge detection algorithm based on fuzzy mathematical morphology[J]. Journal of Hefei University of Technology (Natural Science), 37, 922-927(2014).
[50] Haralick R M, Shanmugam K, Dinstein I. Textural features for image classification[J]. IEEE Transactions on Systems, Man, and Cybernetics, SMC-3, 610-621(1973).
[51] Lowe D G. Object recognition from local scale-invariant features[C], 1150-1157(2002).
[52] Bay H, Ess A, Tuytelaars T et al. Speeded-up robust features (SURF)[J]. Computer Vision and Image Understanding, 110, 346-359(2008).
[53] Shao S L. Research on tobacco stem detection and tobacco type identification method based on machine vision[D](2013).
[54] Cui Y Y. Research and application of cigarette appearance quality detection algorithm[D](2021).
[55] Li R L, Liu Y Y, Li W W et al. Study on rapid determination of tobacco blending uniformity by Near Infrared Spectroscopy[J]. Food & Machinery, 35, 83-87(2019).
[56] Sahu A, Dante H. Non-destructive rapid quality control method for tobacco grading using visible near-infrared hyperspectral imaging[J]. Proceedings of SPIE, 10656, 1065603(2018).
[57] Marcelo M C A, Soares F F, Ardila J A et al. Fast inline tobacco classification by near-infrared hyperspectral imaging and support vector machine-discriminant analysis[J]. Analytical Methods, 11, 1966-1975(2019).
[58] Divyanth L G, Chakraborty S, Li B et al. Non-destructive prediction of nicotine content in tobacco using hyperspectral image-derived spectra and machine learning[J]. Journal of Biosystems Engineering, 47, 106-117(2022).
[59] Duan J, Huang Y, Li Z H et al. Determination of 27 chemical constituents in Chinese southwest tobacco by FT-NIR spectroscopy[J]. Industrial Crops and Products, 40, 21-26(2012).
[60] Niu Q F, Yuan Q, Jin Y et al. Tobacco type recognition based on improved VGG16 convolutional neural network[J]. Foreign Electronic Measurement Technology, 41, 149-154(2022).
[61] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 60, 84-90(2017).
[62] Szegedy C, Liu W, Jia Y Q et al. Going deeper with convolutions[C](2015).
[64] Zeng T, Liu Y X, Jiang Y F et al. Advanced Materials Design for Adsorption of Toxic Substances in Cigarette Smoke[J]. ADVANCED SCIENCE, 10, 2301834(2023).
[65] Gao Z Y, Wang A, Dong H et al. Identification of tobacco components in cut filler based on convolutional neural network[J]. Tobacco Science & Technology, 50, 68-75(2017).
[66] Hu S L, Chen J Q, Lai D H et al. Method for detecting unqualified leaf stem tobacco based on machine vision[J]. Journal of Computer Applications, 39, 215-218(2019).
[67] LeCun Y, Bengio Y, Hinton G. Deep learning[J]. Nature, 521, 436-444(2015).
[69] Men C. A new chapter of packaging printing inspection:machine vision[J]. Printing Field, 59-61(2017).
[70] Li Z J, Li P X, Zhu C. Application of label defect detection system based on deep learning[J]. Modern Electronics Technique, 42, 153-156(2019).
[71] Li Z Z. Research on unsupervised defect detection algorithm of product surface[D](2020).
[72] Shan Y X, Long T, Lou W D et al. A detection and recognition method of cigarette cases in complex scene based on deep learning[J]. Acta Tabacaria Sinica, 27, 71-80(2021).
[73] Zhang W J. Identification and detection of tobacco diseases based on convolutional neural network[D](2021).
[74] Zhang W J, Sun X P, Qiao Y L et al. Tobacco disease identification based on InceptionV3[J]. Acta Tabacaria Sinica, 27, 61-70(2021).
[75] Xie Y R, Miao S, Zhang S et al. Research on tobacco disease identification based on residual neural network[J]. Modern Computer, 27-31(2020).
[76] Wang P. Identification of tobacco leaf disease based on transfer learning[J]. The World of Inverters, 77-80, 89(2018).
[77] Yu J J, Zhou J P, Xue R L et al. Weld surface quality detection based on structured light vision and illumination model[J]. Chinese Journal of Lasers, 49, 1602019(2022).
[78] Liu C W, Duan F J, Li J et al. A scanning direction calibration method of line-structured light three-dimensional sensors[J]. Chinese Journal of Lasers, 50, 0504001(2023).
[79] Zhang J P, Qin X P, Yuan J X et al. Defect location and size detection based on laser ultrasonic diffraction bulk wave[J]. Acta Optica Sinica, 40, 1214002(2020).
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Yusheng Wu, Anhu Li, Yaming Wan, Tianchen Meng. Progress in Research on Tobacco Online Inspection Technology Based on Machine Vision[J]. Laser & Optoelectronics Progress, 2024, 61(8): 0800003
Category: Reviews
Received: May. 18, 2023
Accepted: Jun. 20, 2023
Published Online: Mar. 5, 2024
The Author Email: Wu Yusheng (21480276@qq.com), Li Anhu (lah@tongji.edu.cn)