Automathic visual inspection of a flexographic process using artificial vision to correct the printing plates misalignment
Keywords:
Artificial Vision, Flexography, Printing plates, OpenCV, StroboscopicAbstract
The flexography is an industrial printing method used in different materials such as paper, fabric, cardboard etc, where the alignment of the different printed figures depend on of sync between the printing plates. This work develops a solution through artificial vision and industrial automation this allows knowing the printing plates misalignment in the flexography process, which is realized by the Familia Sancela S.A company. Having as basis a template image, is obtained of way automatic intensity color information through of k-means clustering. This allows making segmentation of the acquired image in real-time process through a high-speed industrial camera and stroboscopic lighting system so, getting from template matching process datas such as location of each object, distance and angles between both these are compared with the information of the image template this allows know quickly and efficiently the distance it has to travel automatically the actuator might locate in the printing plates for a final product of high quality and largely avoid the wastage of paper. In the partial results obtained, the methodology of artificial vision proposal generates a recognition rate and interpretation near to 98%, and in addition provides an easily interpretable result for the actuator work.
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References
[2] Batchelor, B. G., & Whelan, P. F. Intelligent vision systems for industry. City. Retrieved from http://www.citeulike.org/group/2706/article/1389354, 2002.
[3] Kipphan, H. Handbook of Print Media. Handbook of Print Media (p. 1173). doi:10.1007/978-3-540-29900-4, 2001.
[4] H. Kirrmann. Industrial Automation, 1–36. doi:10.1016/B978-0-12-800939- 0/00001-2, 2005.
[5] Kanungo, T., Mount, D. M., Netanyahu, N. S., Piatko, C. D., Silverman, R., & Wu, a. Y. (2002). An efficient k-means clustering algorithm: analysis and implementation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(7), 881–892. doi:10.1109/ TPAMI.2002.1017616
[6] Gonzalez, R. C., & Woods, R. E. Digital Image Processing (p. 976). doi:10.1049/ ep.1978.0474, 2007.
[7] Newman, T. S., & Jain, A. K. A Survey of Automated Visual Inspection. Computer Vision and Image Understanding. doi:10.1006/cviu.1995.1017 , 1995.
[8] Peterson, C. How it works: the charged-coupled device, or CCD. Retrieved from http://legacy.jyi.org/volumes/volume3/issue1/features/peterson.html , 2001.
[9] Sonka, M., City, I., Hlavac, V., & Boyle, R. Image Processing , Analysis , and Machine Vision (p. 856). Cengage Engineering, 2013.
[10] Venkatesan, S., & Karnan, M. Industrial Automation. Articlesbase.com, pp. 1–36. doi:10.1016/B978-0-12-800939-0/00001-2, 2001.
[11] Cao, B., Shen, X., & Qian, Q. Research of flexographic printing dot measurement instrument based on adaptive background method. 9th International Conference on Computer-Aided Industrial Design and Conceptual Design: Multicultural Creation and Design - CAIDCD 2008, 623–627. http://doi.org/10.1109/CAIDCD.2008.4730644 , 2008.
[12] Dendge, R. Minimizing the Print Quality Limitations During Selection of Anilox Roll Line Frequency in Flexographic Half Tone Printing, 107–111, 2014.
[13] Gil Barros, G. Influence of Substrate Topography on Ink Distribution in Flexography, Dissertation, Karlstad university, Karlstad, Sweden, 2006.
[14] M. Rentzhog “Water-Based Flexographic Printing on Polymer-Coated Board”. Tesis de doctorado en el Royal Institute of Technology, Stockholm, Sweden, http://pdfshares.net/file/1FD1/water-based-flexographic-printing-on-polymer-coated-board.html 2006.
[15] Z. Żołek-Tryznowska, J. Izdebska, M. Tryznowski “Branched polyglycerols as performance additives for water-based flexographic printing inks. Progress in Organic Coatings” Vol. 78, Pg. 334–339. http://doi.org/10.1016/j.porgcoat.2014.07.015, 2015.
[16] P. Bartoloa, M. Domingosa, A. Gloriab, J. Ciuranac. “BioCell Printing: Integrated automated assembly system for tissue engineering constructs” CIRP Annals - Manufacturing Technology. Vol. 60, Iss. 1, Pg 271–274, 2011.
[17] A. Likas, N. Vlassis, J.J. Verbeek. “Patlern Recognition”. Ed. Elsevier Vol. 36, Iss. 2. Pg 451-461, 2003.
[18] J. A. Hartigan, M. A. Wong “A K-Means Clustering Algorithm”. Journal of the Royal Statistical Society, Vol. 28 Iss. 1, Pg. 100–108. http://doi.org/10.2307/2346830 , 1979.
[19] Ma, L, Sun, Feng, N & Liu, Z. Image Font Template Matching Algoritm Based on proyection and sequential similiosity detecting figth International conference on inteligent information hiding and multimedia signal processing, 2009.
[20] OpenCV. The OpenCV User Guide. OpenCV, 2012.
