Researching | Intelligent Detection and Defect Classification of Infusion Bags Based on Support Vector Machine

Journals >Laser & Optoelectronics Progress >Volume 56 >Issue 13 >Page 131502 > Article

Laser & Optoelectronics Progress
Vol. 56, Issue 13, 131502 (2019)

Intelligent Detection and Defect Classification of Infusion Bags Based on Support Vector Machine

Dan Li^*, Yuanyuan Jin, Yan Tong, Guojun Bai, and Ming Yang

Author Affiliations

Department of Information and Control Engineering, Shenyang Urban Construction University, Shenyang, Liaoning 110167, China

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DOI: 10.3788/LOP56.131502 Cite this Article Set citation alerts

Dan Li, Yuanyuan Jin, Yan Tong, Guojun Bai, Ming Yang. Intelligent Detection and Defect Classification of Infusion Bags Based on Support Vector Machine[J]. Laser & Optoelectronics Progress, 2019, 56(13): 131502 Copy Citation Text

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References

[1] Tian M, Liu Q X. Method of print defects detection based on sub-region and grading[J]. Packaging Engineering, 36, 122-127(2015).

[2] Guan Y Y, Ye Y C. Printing defects detection based on two-times difference image method[J]. Applied Mechanics and Materials, 340, 512-516(2013). http://www.scientific.net/AMM.340.512

[3] Xu M, Tang W Y, Ma Q L et al. Research of printing defect on-line detection based on Blob algorithm[J]. Packaging Engineering, 32, 20-23, 80(2011).

[4] Hu F S, Guo H, Xing J P et al. Image registration based on label printing defect detection[J]. Optical Technique, 43, 16-21(2017).

[5] Wang H L, Zhao B H, Sun Z Q et al. Defect detection of medical bags based on HALCON[J]. Packaging Engineering, 36, 125-129(2015).

[6] Guo M, Hu L L, Zhao J T. Surface defect detection method of ceramic bowl based on Kirsch and Canny operator[J]. Acta Optica Sinica, 36, 0904001(2016).

[7] Vapnik V N. The nature of statistical learning theory[M]. New York: Springer(1995).

[8] Mao Z C, Chen Q. Recognition and tracking of AGV multi-branch path based on PCA-LDA and SVM[J]. Laser & Optoelectronics Progress, 55, 091005(2018).

[9] Yang Y S, Zhang Y, Yang Y L et al. Qualitative analysis of molten steel based on support vector machine by LIBS[J]. Laser & Optoelectronics Progress, 52, 053001(2015).

[10] Huang Z H, Mao J X, Wang Y N et al. Research on beer bottle defect classification detection method based on machine vision[J]. Journal of Electronic Measurement and Instrumentation, 30, 873-879(2016).

[11] Shu W P, Liu Q X. Classification method of printing defects based on support vector machine[J]. Packaging Engineering, 35, 138-142(2014).

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Dan Li, Yuanyuan Jin, Yan Tong, Guojun Bai, Ming Yang. Intelligent Detection and Defect Classification of Infusion Bags Based on Support Vector Machine[J]. Laser & Optoelectronics Progress, 2019, 56(13): 131502

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