A Survey on Various Approaches of Automatic Optical Inspection for PCB Defect Detection

Authors

  • Kumar M Department of Electronics and Communication Engineering and Sant Longowal Institute of Engineering and Technology, Longowal, Punjab
  • Kumar M Suncity Enterprises, Jaipur

DOI:

https://doi.org/10.26438/ijcse/v7i6.837841

Keywords:

PCB, Automated Visual inspection, Machine Vision, Image processing, Referential, Non-referential, Hybrid approach

Abstract

The Printed circuit board (PCB) is one of the crucial components of the electronics industry. An automated visual inspection system is required to provide a fast and quantitative assessment of PCB, since manual defect detection system is not efficient and time-consuming. Machine vision technology is an alternative to manual inspections and measurements with the help of high-resolution digital camera and image processing. This paper presents the various possible defects in PCB that can affect the working of electronic gadgets. Major defects are classified mainly under Fatal and Potential that can be detected mainly by any of the three approaches as Referential, Non-referential, and, Hybrid to find out defects present in PCB. After a comparative study of these methods, we have tried to find out the significantly fast and accurate method.

References

[1] M. Kumar, N. Kumar, M. Kumar, Ajay Kumar Vishwakarma, “A Novel Approach of Standard Data Base Generation for Defect Detection in Bare PCB”, in the IEEEinternational conference on ICCCA, 2015, pp. 11-15, 2015.

[2] M. Kumar, M. Kumar, G. Kumar, “PCB Image Enhancement using Machine Vision for Effective Defect Detection”, international Journal of Advanced Engineering Research and Science (IJAERS) Vol-1, Issue-3, pp.50-53, Aug- 2014.

[3] A. eohong, Z.B. Ibrahim, S. Ramli, “Computer machine vision inspection on Printed Circuit Board flux defects”, American Journal of Engineering and Applied Sciences, Science Publication, Vol-6, Issue-3, pp.263-273, 2013.

[4] Y. hanlin, W. jun., “Automatic detection method of Circuit Boards defect based on partition enhanced matching”, Information Technology Journal, Vol-11, pp.2256-2260, 2013.

[5] T.J. Mateo Sanguino and M.S. Rodriguez, “Computer-Aided System for Defect Inspection in the PCB Manufacturing Process”, In the 16th IEEE International Conference on Intelligent Engineering Systems, pp. 151-156. 2012.

[6] Z. Li, Q. Yang, “System design for PCB defects detecion based on AOI technology”, In IEEE, International Congress on Image and Signal Processing, Vol-4, pp.1988-1992, 2011.

[7] F. Guo, S. Guan,” Research of the Machine Vision Based PCB Defect Inspection System”, In IEEE International Conference on Intelligence Science and Information Engineering, pp. 472-475, 2011.

[8] S. Guan, F. Guo, “A New Image Enhancement Algorithm for PCB Defect Detection”, In IEEE International Conference on Intelligence Science and Information Engineering, pp.454-456 2011.

[9] Z. Ibrahim, N.K. Khalid, I. Ibrahim, M.S. Zainal Abidin, M.M. Mokji, S. A. Rahman Syed Abu Bakar,” A noise elimination procedure for Printed Circuit Board inspection system” In the 2nd IEEE Asia International Conference on Modelling & Simulation, pp. 332-33, 2008.

[10] S. Mashohor, J.R. Evans, A.T. Erdogan “Automatic Hybrid Genetic Algorithm Based Printed Circuit Board Inspection” In the IEEE NASA/ESA Conference on Adaptive Hardware and Systems, pp. 390-400, 2006.

[11] Z. Ibrahim , S.A.R Al-Attas, O. Ono, and M.M. Mokji, “A noise elimination procedure for Wavelet-Based Printed Circuit Board inspection system”, Asian Control Conference, pp. 875-880, 2004

[12] J.J. Hong, K.J. Park, K.G. Kim “Parallel Processing Machine Vision System for Bare PCB Inspection”, In IECON`98, Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society, Vol. 3, pp. 1346-1350, 1998.

[13] M. Moganti., F. Ercal, S. Tsunekaw,“Automatic PCB inspection algorithms: A Survey”, Computer vision and image understanding, Vol.63, pp. 287–313, 1996.

[14] T.S. Newman, A.K. Jain,“A Survey of Automated Visual inspection”, Computer vision and image understanding, Vol. 61, pp. 231-262,1995.

[15] Y. Hara., N. Akiyana, and K. Kaasaki , “Automatic inspection system for Printed Circuit Boards”, IEEE Transactions on pattern analysis and Machine intelligence, Vol. 6, pp. 623-630, 1983.

[16] F.R. Leta, F.F. Feliciano, F.P. Martins “Computer vision system for Printed Circuit Board inspection”, ABCM Symposium Series in Mechatronics, Volume 3, pp. 623-632, 2008.

Downloads

Published

2019-06-30
CITATION
DOI: 10.26438/ijcse/v7i6.837841
Published: 2019-06-30

How to Cite

[1]
M. Kumar and M. Kumar, “A Survey on Various Approaches of Automatic Optical Inspection for PCB Defect Detection”, Int. J. Comp. Sci. Eng., vol. 7, no. 6, pp. 837–841, Jun. 2019.

Issue

Vol. 7 No. 6 (2019): IJCSE June Edition

Section

Survey Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.