Chains Defects Detection in a Printed Circuit Board Image by the Plane Partition and Flood-filling of Traces
DOI:
https://doi.org/10.47839/ijc.22.1.2877Keywords:
printed circuit board, defect detection, chain, contact, pixel, trace, flood-fill, short, open, distributed cumulative histogram, piecewise linear approximation, cumulative histogram, distribution of pixelAbstract
An approach to dividing the printed circuit board into parts to increase visibility of defects in a PCB image is considered. The approach is based on a piecewise linear approximation of a cumulative histogram. The last one is calculated for numbers of informative pixels placed in rows and columns of an image matrix. Informative pixels are those indicating contacts and C traces. The histogram demonstrates a distribution of informative pixels along the OX and OY axes. The beginning and ending points of linear lines are taken as coordinates of the divided parts of the PCB board. The flood-fill algorithm is used to color and separate the PCB chains components. The start pixels are taken from a set of informative pixels. To measure defect values, a mean intensity and gradient functions for the template and manufactured images are used. Distributed cumulative histograms are applied to PCB components to detect places and intensity of defects.
References
D. B. Anitha, M. Rao, “A survey on defect detection in bare PCB and assembled PCB using image processing techniques,” Proceedings of the International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 2017, pp. 39-43. https://doi.org/10.1109/WiSPNET.2017.8299715.
K. P. Anoop, N. S. Sarath, V. V. S. Kumar, “Review of PCB defect detection using image processing,” International Journal of Engineering and Innovative Technology (IJEIT), vol. 4, issue 11, pp. 188-192, 2015.
S. McClure, “Extracting and classifying circuit board defects using image processing and deep learning,” [Online]. Available at: https://towardsdatascience.com/ building-an-end-to-end-deep-learning-defect-classifier-application-for-printed-circuit-board-pcb-361b3a76232.
Seven types of defects, [Online]. Available at: https://blog.matric.com/7-types-of-pcb-soldering-defects-to-watch-out-for.
Visual Fault Analyzer (VFAT) speeds PCB fault Diagnostics and Repair, [Online]. Available at: http://www.intellitech.com/company/
V. A. Adibhatla, H.-C. Chih, C.-C. Hsu, J. Cheng, M. F. Abbod, and J.-S. Shieh, “Defect detection in printed circuit boards using you-only-look-once convolutional neural networks,” Electronics, vol. 9, 1547, 2020. https://doi.org/10.3390/electronics9091547.
Y. Hanlin, W. Jun, “Automatic Detection Method of Circuit Boards Defect Based on Partition Enhanced Matching,” Information Technology Journal, vol. 12, issue 11, pp. 2256-2260, 2013. https://doi.org/10.3923/itj.2013.2256.2260.
J. Zhu, A. Wu, X. Liu, “Printed circuit board defect visual detection based on wavelet denoising,” IOP Conference Series: Materials Science and Engineering, vol. 392, pp. 1-6, 2018. https://doi.org/10.1088/1757-899X/392/6/062055.
F. B. Nadaf, V. S. Kolkure, “Detection of bare PCB defects by using morphology technique,” International Journal of Electronics and Communication Engineering, vol. 9, no. 1, pp. 63-76, 2016.
P. R. J. Nayaka, K. Anitha, B. D. Parameshachari, R. Banud, P. Rashmi “PCB fault detection using image processing,” IOP Conference Series: Materials Science and Engineering, vol. 225, pp. 1-5, 2017. https://doi.org/10.1088/1757-899X/225/1/012244.
R. Melnyk, R. Tushnytskyy, R. Kvit, “Cloudiness images multilevel segmentation by piecewise linear approximation of cumulative histogram,” International Journal of Computing, vol. 19, issue 2, pp. 199–207, 2020. https://doi.org/10.47839/ijc.19.2.1762.
R. Melnyk, Yu. Kalychak, “Detection of defects in printed circuit boards by flood-fill algorithm and distributed cumulative histogram,” Proceedings of the XIII International conference on Computer sciences and information technologies (CSIT-2018), 2018, pp. 155–159. https://doi.org/10.1109/STC-CSIT.2018.8526733.
S. Ganesan, M. Pecht, “Open trace defects in FR4 printed circuit boards,” Circuit World, vol. 32, issue 1, pp. 3-7, 2006. https://doi.org/10.1108/03056120610616490.
Why Do We Use Copper to Make PCB Traces? [Online]. Available at: https://yic-assm.com/why-do-we-use-copper-to-make-pcb-traces/.
A. P. Singh Chauhan, S. C. Bhardwaj, “Detection of bare PCB defects by image subtraction method using machine vision,” Proceedings of the World Congress on Engineering, vol. II, WCE, 2011, pp. 6-8.
Bond, “An Efficient and Versatile Flood Fill Algorithm for Raster Scan Displays,” 2011. [Online]. Available at: www.crbond.com.
K. Kamalpreet, K. Beant, “PCB defect detection and classification using image processing,” International Journal of Emerging Research in Management &Technology, vol. 3, issue 8, pp. 42-46, 2014.
M. H. Tatibana, R. de A. Lotufo, “Novel automatic PCB inspection technique based on connectivity,” Proceedings of the X Brazilian Symposium on Computer Graphics and Image Processing, 1997, pp. 187-194.
M. Moganti, F. Ercal, C. H. Dagli, S. Tzumekawa, “Automatic PCB inspection algorithms: A review,” Computer Vision and Image Understanding, vol. 63, issue 2, pp. 287-313, 1996. https://doi.org/10.1006/cviu.1996.0020.
K. P. Anoop, N. S. Sarath, V. V. Kumar, “A review of PCB defect detection using image processing,” International Journal of Engineering and Innovative Technology (IJEIT), vol. 4, issue 11, pp. 188-192, 2015.
S. H. Putera, Z. Ibrahim, “Printed circuit board defect detection using mathematical morphology and MATLAB image processing tools,” Proceedings of the 2nd International Conference on Education Technology and Computer, 2010, vol. 5, pp. 359-363. https://doi.org/10.1109/WiSPNET.2017.8299858.
F. Vikas Chaudhary, I. R. Dave, K. P. Upla, “Visual inspection of printed circuit board for defect detection and classification,” Proceedings of the International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 2017, pp. 732-737.
Guide to PCB issues. [Online]. Available at: https://www.mclpcb.com/guide-pcb-issues/.
A PCB Dataset, [Online]. Available at: https://www.123rf.com/photo_40192468 computer-chip-showing-high-tech-and-circuit.html.
PCB images, [Online]. Available at: https://www.eleccircuit.com/5-30-minuts-timer-alarm-circuit-using-ic555/.
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