Skip to main content

Advertisement

SpringerLink
Log in

Development of new edge-detection filter based on genetic algorithm: an application to a soldering joint inspection

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

This paper proposes a new technique of edge detection for inspecting edge and perfection of soldering joint in the flip-chip, which is an important part of a hard disk drive. Summation of error between the actual values and the measured values from the designed system of several data sets is formulated as the objective function. Genetic algorithm is adopted to find the optimal filter mask to enhance the accuracy of the inspection system. As the results indicated, the accuracy of a system with the proposed edge-detection technique is superior to that of a system with conventional filters.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Wahler RA, Shih FY (1989) Image enhancement for radiographs utilizing filtering, gray scale transformation and Sobel gradient operator. IEEE Engineering in Medicine and Biology Annual International Conference 2:618–619

    Google Scholar 

  2. Heath M, Sarkar S, Sanocki T, Bowyer KW (1997) A robust visual method for assessing the relative performance of edge-detection algorithms. IEEE Trans Pattern Anal Mach Intell 19(12):1338–1359

    Article  Google Scholar 

  3. Foschi P, Kolippakkam D, Liu H, Mandvikar A (2002) Feature extraction for image mining. Proceedings of the International Workshop on Multimedia Information Systems (MIS), pp 103–109

  4. Nezamabadi-pour H, Saryazdi S (2006) Edge detection using ant algorithm. Soft Comput 10:623–628

    Article  Google Scholar 

  5. Kaitwanidvilai S, Saenthon A (2008) Automatic visual inspection of bump in hard disk drive component using neural network and image processing. Proceedings of the IASTED International Conference on Computer Graphic and Imaging, Austria, pp 112–116

  6. Karnprachar S, Saenthon A, Kaitwanidvilai S (2007) A nondestructive bump inspection in flip chip component using fuzzy image filtering. ECTI Transactions on Electrical Engineering, Electronics, and Communications (ECTI-EEC), vol. 5, no. 2

  7. Erus G, Lomenie N (2007) Classification of structural cartographic objects using edge-based features. Lect Notes Comput Sci 4841:385–392

    Article  Google Scholar 

  8. Holland JH (1975) Adaptation in neural and artificial system. The University of Michigan Press, Ann Arbor

    Google Scholar 

  9. De G (1989) Genetic algorithms in search optimization, and machine learning. Addison-Wesley, Reading

    Google Scholar 

  10. Gen M, Cheng R (2000) Genetic algorithms and engineering optimization. Wiley, New York

    Google Scholar 

  11. Lee Y et al (2004) A robust approach to edge detection of scanned point data. Int J Adv Manuf Technol 23:263–271

    Article  Google Scholar 

  12. Liu X, Begg DW, Fishwisk RJ (1998) Genetic approach to optimal topology/controller design of adaptive structures. Int J Number Methods Eng 41(5):815–830

    Article  MATH  Google Scholar 

  13. Dorsey RE, Mayer WJ (1995) Genetic algorithm for estimation problem with multiple optima, non-differentiability, and other irregular. J Bus Econ Stat 13(1):53–66

    Article  Google Scholar 

  14. Bhandarker M, Zhang Y, Potter D (1993) A genetic algorithm-based edge detection technique. Proceedings of IJNN, IEEE, pp 2995–2999

  15. Wang Y, Funakubo N (1996) Detection of geometric shapes by the combination of genetic algorithm and subpixel accuracy. Proceedings of ICPR, IEEE, pp 535–539

  16. Gudmundsson M, El-Kwae EA, Kabuka MR (1998) Detection in medical images using a genetic algorithm. IEEE Trans Med Imag 17:469–474

    Article  Google Scholar 

  17. Lee MK, Leung SW, Pun TL, Cheung HL, Lee AMK (2000) Edge detection by genetic algorithm. Proceedings of ICIP, IEEE 1:478–480

    Google Scholar 

  18. Dao S, De Natale GB (2003) Edge potential functions and genetic algorithms for shape-based image retrieval. Proceeding of ICIP, IEEE 3:729–732

    Google Scholar 

  19. Min W, Shuyuan Y (2005) A hybrid genetic algorithm-based edge detection method for SAR image. Proceedings of the Radar Conference, IEEE International, pp 503–506

  20. Li BB, Zhang Y (2007) An adaptive immune genetic algorithm fog edge detection. ICIC, LNAI 4682:565–571

    Google Scholar 

  21. Gonzalez RC, Wood RE (2002) Digital image processing, 2nd edn. Addison-Wesley, Boston, pp 572–607

    Google Scholar 

  22. Pratt WK (2007) Digital imaging processing, 4th edn. Wiley, New York

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, 10520, Thailand

    A. Saenthon

  2. Center of Excellence for Innovative Energy Systems, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, 10520, Thailand

    S. Kaitwanidvilai

Authors
  1. A. Saenthon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. Kaitwanidvilai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. Saenthon.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Saenthon, A., Kaitwanidvilai, S. Development of new edge-detection filter based on genetic algorithm: an application to a soldering joint inspection. Int J Adv Manuf Technol 46, 1009–1019 (2010). https://doi.org/10.1007/s00170-009-2157-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-009-2157-x

Keywords

Search

Navigation