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A Comparative Study of Automated PCB Defect Detection Algorithms and to Propose an Optimal Approach to Improve the Technique

by Mohit Borthakur, Anagha Latne, Pooja Kulkarni
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 114 - Number 6
Year of Publication: 2015
Authors: Mohit Borthakur, Anagha Latne, Pooja Kulkarni
10.5120/19985-1938

Mohit Borthakur, Anagha Latne, Pooja Kulkarni . A Comparative Study of Automated PCB Defect Detection Algorithms and to Propose an Optimal Approach to Improve the Technique. International Journal of Computer Applications. 114, 6 ( March 2015), 27-33. DOI=10.5120/19985-1938

@article{ 10.5120/19985-1938,
author = { Mohit Borthakur, Anagha Latne, Pooja Kulkarni },
title = { A Comparative Study of Automated PCB Defect Detection Algorithms and to Propose an Optimal Approach to Improve the Technique },
journal = { International Journal of Computer Applications },
issue_date = { March 2015 },
volume = { 114 },
number = { 6 },
month = { March },
year = { 2015 },
issn = { 0975-8887 },
pages = { 27-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume114/number6/19985-1938/ },
doi = { 10.5120/19985-1938 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:52:01.665631+05:30
%A Mohit Borthakur
%A Anagha Latne
%A Pooja Kulkarni
%T A Comparative Study of Automated PCB Defect Detection Algorithms and to Propose an Optimal Approach to Improve the Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 114
%N 6
%P 27-33
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Automated visual printed circuit board (PCB) inspection is an approach used to counter difficulties occurred in manual inspection that can eliminate subjective aspects and then provide fast, quantitative, and dimensional assessments. Various concentrated work on detection of defects of printed circuit boards (PCBs) have been done, but it is also crucial to classify these defects in order to analyze and identify the root causes of the defects. However, besides the need to detect the defects, it is also essential to classify these defects so that the source of these defects can be identified. Based on studies done till now, some PCB defects can only exist in certain groups. Thus, it is obvious that the image processing algorithm could be improved by applying a segmentation exercise. This paper makes a comparative study of all such algorithms developed till date, to analyze their shortcomings and thereby provide an optimal approach to detect maximum of the defects with higher accuracy as well as with speed. This approach uses morphological image segmentation algorithm and simple image processing theories. The given algorithm can overcome most of the defects of previous algorithms and detect more than 80% of defects in a given PCB which ranges from missing components, broken tracks, misplaced components etc.

References
  1. F. Moganti, F. Ercal, C. H. Dagli, S. Tsunekawa. "Automatic PCB inspection algorithms:A survey, Computer Vision and Image Understanding", Vol. 63,No. 2, pp. 287-313, 1996.
  2. Wen-Yen, J. Mao-Jiun, J. Wang, L. Chih-Ming. "Automated inspection of printed circuit board through machine vision, Computers in Industry", Vol. 28, Issue 2, pp. 103-111, 1996.
  3. J. H. Koo, S. I. Yoo. "A structural matching for two-dimensional visual pattern inspection, IEEE International Conference on Systems, Man, and Cybernatics", Vol. 5, pp. 4429-4434, 1998.
  4. M. H. Tatibana, R. de A. Lotufo. "Novel automatic PCB inspection technique based on connectivity,Proceedings of Brazilian Symposium on Computer Vision and Image Pro cessing", pp. 187-194, 1997.
  5. M. Ouslim, K. M. Curtis. "PCB inspection based on a variant of the N-tuple technique, Fifth International Conference on Image Processing and its Applications",pp. 677-681,1995.
  6. F. Ercal, F. Bunyak, H. Feng, L. Zheng. "A fast modular RLE-based inspection scheme for PCBs,Proceedings of SPIE Architectures, Networks and Intelligent Systems for Manu facturing Integration", Vol. 3203, pp. 45-59, 1997.
  7. F. Ercal, F. Bunyak, H. Feng. " Context-sensitive filtering in RLE for PCB inspection,Proceedings of SPIE Intelligent Systems and Advanced Manufacturing", Vol. 3517, 1998.
  8. F. Ercal, M. Allen, H. Feng. "Proof of correctness and performance analysis of a systolic image difference algorithm for RLE-compressed images, IEEE Transaction on Parallel and Distributed Computing Systems", Vol. 11, No. 5, pp. 433-443, 2000.
  9. S. H. Oguz, L. Onural. " An automated system for design-rule-based visual inspection of printed circuit boards, Proceedings of the IEEE International Conference on Robotics and Automation", pp. 2696-2701, 1991.
  10. A. M. Darwish, A. K. Jain. " A rule based approach for visual pattern inspection, IEEE Transaction of Pattern Analysis and Machine Intelligence", Vol. PAMI-10, No. 1, pp. 56-58, 1988.
  11. Y. Qin-Zhong, P. E. Danielson. "Inspection of printed circuit boards by connectivity preserving shrinking, IEEE Transaction on Pattern Analysis and Machine Intelligence", Vol. PAMI-10, No. 5.
  12. Zuwairie Ibrahim, Syed Abdul Rahman Al-Attas and Zulfakar Aspar," Model-based PCB Inspection Technique Using Wavelet Transform", The 4th Asian Control Conference, Singapore, pp. 55-58, 2002.
  13. Hamed Kiani, Reza Safabakhsh, Ehsan Khadangi. "Fast Recursive Segmentation Algorithm Based on Kapur's Entropy".
  14. Sanveer Singh, Manu Bharti," Image Processing Based Automatic Visual Inspection System for PCBs", IOSR Journal of Engineering (IOSRJEN) ISSN: 2250-3021 Volume 2, Issue 6 ,PP 1451-1455, June 2012.
  15. D. M. Tsai and Y. H. Chen, "A fast histogram-clustering approach for multilevel thresholding," Pattern Recognition Letters, Vol. 13, No. 4, 1992, pp. 245-252.
  16. J. C. Yen, F. J. Chang, and S. Chang, "A new criterion for automatic multilevel thresholding,"IEEE Transactions on Image Processing, Vol. 4, No. 3, 1995, pp. 370-378.
  17. Dr. Philippe Cattin (2012-04-24). "Image Restoration: Introduction to Signal and Image Processing". MIAC, University of Basel. Retrieved 11 October 2013.
  18. Jayaraman et al. (2009). Digital Image Processing. Tata McGraw Hill Education. p. 272.
Index Terms

Computer Science
Information Sciences

Keywords

PCB Testing Digital Image Processing Morphological Operators Pattern Classification Wavelet Transform

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