Skip to main content
SpringerLink
Log in

Enhancing an Automated Inspection System on Printed Circuit Boards Using Affine-SIFT and TRIZ Techniques

  • Conference paper
Advances in Visual Informatics (IVIC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8237))

Included in the following conference series:

Abstract

Automated visual inspection is an important step to assure the quality of printed circuit boards (PCB). Component placement errors such as missing, misaligned or incorrectly rotated component are major causes of defects on surface mount PCB. This paper proposes a novel automated visual inspection method for PCB. The proposed method uses a sequence of image processing techniques inspired by the theory of inventive problem solving (TRIZ) with Affine-SIFT image matching techniques to enhance the component placement inspection. Only analytic discussions are presented in this paper to support the potential of the proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Chuang, S.-F., Chang, W.-T., Lin, C.-C., Tarng, Y.-S.: Misalignment inspection of multilayer PCBs with an automated X-ray machine vision system. The International Journal of Advanced Manufacturing Technology 51, 995–1008 (2010)

    Article  Google Scholar 

  2. Perng, D.-B., Liu, H.-W., Chang, C.-C.: Automated SMD LED inspection using machine vision. The International Journal of Advanced Manufacturing Technology 57, 1065–1077 (2011)

    Article  Google Scholar 

  3. Zeng, Z., Ma, L.Z., Zheng, Z.Y.: Automated extraction of PCB components based on specularity using layered illumination. Journal of Intelligent Manufacturing 22, 919–932 (2011)

    Article  Google Scholar 

  4. Wu, C.-H., Wang, D.-Z., Ip, A., Wang, D.-W., Chan, C.-Y., Wang, H.-F.: A particle swarm optimization approach for components placement inspection on printed circuit boards. Journal of Intelligent Manufacturing 20, 535–549 (2009)

    Article  Google Scholar 

  5. Chu, C., Wang, C., Jiang, B.: An Automatic Image Enhancement Framework for Industrial Products Inspection. In: Proceedings of the Institute of Industrial Engineers Asian Conference, pp. 73–78. Springer (2013)

    Google Scholar 

  6. Mogharrebi, M., Prabuwono, A.S., Sahran, S., Aghamohammadi, A.: Missing Component Detection on PCB Using Neural Networks. In: Zheng, D. (ed.) Advances in Electrical Engineering & Electrical Machines. LNEE, vol. 134, pp. 387–394. Springer, Heidelberg (2012)

    Google Scholar 

  7. Mar, N.S.S., Yarlagadda, P., Fookes, C.: Design and development of automatic visual inspection system for PCB manufacturing. Robotics and Computer-Integrated Manufacturing 27, 949–962 (2011)

    Article  Google Scholar 

  8. Ang, M.C., Pham, D.T., Soroka, A.J., Ng, K.W.: PCB assembly optimisation using the Bees Algorithm enhanced with TRIZ operators. In: IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society, pp. 2708–2713 (2010)

    Google Scholar 

  9. Altshuller, G.: The innovation algorithm: TRIZ, systematic innovation and technical creativity. Technical Innovation Ctr, Worcester (1999)

    Google Scholar 

  10. Ahmad, S.A., Pham, D.T., Ng, K.W., Ang, M.C.: TRIZ-inspired Asymmetrical Search Neighborhood in the Bees Algorithm. In: 2012 Sixth Asia Modelling Symposium (AMS). IEEE (2012)

    Google Scholar 

  11. Yu, G., Morel, J.-M.: A fully affine invariant image comparison method. In: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2009. IEEE (2009)

    Google Scholar 

  12. Newcombe, R.A., Davison, A.J.: Live dense reconstruction with a single moving camera. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE (2010)

    Google Scholar 

  13. Ta, D.-N., Chen, W.-C., Gelfand, N., Pulli, K.: SURFTrac: Efficient tracking and continuous object recognition using local feature descriptors. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009. IEEE (2009)

    Google Scholar 

  14. Doubek, P., Matas, J., Perdoch, M., Chum, O.: Image matching and retrieval by repetitive patterns. In: 2010 20th International Conference on Pattern Recognition (ICPR). IEEE (2010)

    Google Scholar 

  15. Morel, J., Yu, G.: Is SIFT scale invariant? Inverse Problems and Imaging 5, 115–136 (2011)

    Article  MATH  Google Scholar 

  16. Morel, J.-M., Yu, G.: ASIFT: A new framework for fully affine invariant image comparison. SIAM Journal on Imaging Sciences 2, 438–469 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  17. Lowe, D.G.: Object recognition from local scale-invariant features. In: The Proceedings of the Seventh IEEE International Conference on Computer Vision. IEEE (1999)

    Google Scholar 

  18. Oji, R.: An Automatic Algorithm for Object Recognition and Detection Based on ASIFT Keypoints, arXiv preprint arXiv:1211.5829 (2012)

    Google Scholar 

  19. Yu, G., Morel, J.-M.: ASIFT: An Algorithm for Fully Affine Invariant Comparison. Image Processing On Line (2011)

    Google Scholar 

  20. Su, Y.-Y., Srihari, K.: Placement sequence identification using artificial neural networks in surface mount PCB assembly. The International Journal of Advanced Manufacturing Technology 11, 285–299 (1996)

    Article  Google Scholar 

  21. Dong, N., Wu, C.-H., Ip, W.-H., Chen, Z.-Q., Yung, K.-L.: Chaotic species based particle swarm optimization algorithms and its application in PCB components detection. Expert Systems with Applications (2012)

    Google Scholar 

  22. Wu, H., Kuang, Y., Ouyang, G., Xie, H., Zhang, X.: Optimize Position and Path Planning of Automated Optical Inspection. Journal of Computational Information Systems 8, 2957–2963 (2012)

    Google Scholar 

  23. Dong, Z.-J., Ye, F., Li, D., Huang, J.-X.: PCB matching based on SURF. Circuit World 38, 153–162 (2012)

    Google Scholar 

  24. Crispin, A., Rankov, V.: Automated inspection of PCB components using a genetic algorithm template-matching approach. The International Journal of Advanced Manufacturing Technology 35, 293–300 (2007)

    Article  Google Scholar 

  25. Cho, H.-J., Park, T.-H.: Wavelet transform based image template matching for automatic component inspection. The International Journal of Advanced Manufacturing Technology 50, 1033–1039 (2010)

    Article  Google Scholar 

  26. Wu, C., Dong, N., Ip, W., Chen, Z., Yung, K.: Applying Chaotic Particle Swarm Optimization to the Template Matching Problem. In: Cai, Z., Li, Z., Kang, Z., Liu, Y. (eds.) ISICA 2009. LNCS, vol. 5821, pp. 411–421. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  27. Xie, F., Uitdenbogerd, A., Song, A.: Detecting PCB component placement defects by genetic programming. In: Congress on Evolutionary Computation (CEC), pp. 1138–1145. IEEE (2013)

    Google Scholar 

  28. Jean, M.M., Guoshen, Y.: SIFT and ASIFT — online demo: try if your images match! (2011), http://www.cmap.polytechnique.fr/~yu/research/ASIFT/demo.html , http://demo.ipol.im/demo/my_affine_sift/

Download references

Author information

Authors and Affiliations

  1. Institute of Visual Informatics (IVI), National University of Malaysia (UKM), Malaysia

    Amirhossein Aghamohammadi, Mei Choo Ang & Marzieh Mogharrebi

  2. Faculty of Information Science and Technology, National University of Malaysia (UKM), Malaysia

    Anton Satria Prabuwono

  3. Design Engineering Section, Industrial Design Centre, Sirim Berhad, Bukit Jalil, Kuala Lumpur, Malaysia

    Kok Weng Ng

Authors
  1. Amirhossein Aghamohammadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mei Choo Ang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Anton Satria Prabuwono
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Marzieh Mogharrebi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kok Weng Ng
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Visual Informatics, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia

    Halimah Badioze Zaman

  2. Computer Laboratory, University of Cambridge, CB3 0FD, Cambridge, UK

    Peter Robinson

  3. School of Computing Science, Newcastle University, Culture Lab, King’s Walk, NE1 7RU, Newcastle Upon Tyne, UK

    Patrick Olivier

  4. Dept. of Computer Science and Information Engineering, National Central University, No 300, Jhongda Rd, Jhongli, Taiwan

    Timothy K. Shih

  5. Computing and Information Systems, Kingston University, Penrhyn Road, Kingston upon Thames, KT1 2EE, London, United Kingdom

    Sergio Velastin

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer International Publishing Switzerland

About this paper

Cite this paper

Aghamohammadi, A., Ang, M.C., Prabuwono, A.S., Mogharrebi, M., Ng, K.W. (2013). Enhancing an Automated Inspection System on Printed Circuit Boards Using Affine-SIFT and TRIZ Techniques. In: Zaman, H.B., Robinson, P., Olivier, P., Shih, T.K., Velastin, S. (eds) Advances in Visual Informatics. IVIC 2013. Lecture Notes in Computer Science, vol 8237. Springer, Cham. https://doi.org/10.1007/978-3-319-02958-0_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-02958-0_12

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-02957-3

  • Online ISBN: 978-3-319-02958-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation