Transactions of Materials Processing (소성∙가공)

The Korean Society for Technology of Plasticity and materials processing (한국소성∙가공학회)
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Application of Image Processing Technique to Improve Production Efficiency of Fine Pitch Hole Based on Laser

레이저 미세피치 홀 가공의 생산효율성 향상을 위한 영상처리 측정 기법 적용

  • Received : 2010.04.12
  • Accepted : 2010.07.28
  • Published : 2010.08.01
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Abstract

Multi-Layer Ceramic Circuit(MLCC) in the face of thousands of fine pitch multi hole is processed. However, the fine pitch multi hole has a size of only a few micrometers. Therefore, in order to curtail the measurement time and reduce error, the image processing measurement method is required. So, we proposed an image processing measurement algorithm which is required to accurately measure the fine pitch multi hole. The proposed algorithm gets image of the fine pitch multi hole, extracts object from the image by morphological process, and extracts the parameters of its position and feature by edge detecting process. In addition, we have used the sub-pixel algorithm to improve accuracy. As a result, the proposed algorithm shows 97% test-retest measurement reliability within 2 ${\mu}m$. We found that the algorithm was wellsuited for measuring the fine pitch multi hole.

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References

  1. K. Kawahara, Y. Shidama, T. Muyazaki, Y. Nakamura and H. Yamaura, 1997, Image Processing with Topology and Mathematical Morphology, IEICE Trans. D II, No.1, pp. 166-174.
  2. K. Ikeuchi and T. Kanade, 1998, Automatic Generation of Object Recognition Program, Proc. of the IEEE, Vol. 76, No. 8, pp. 1016-1035. https://doi.org/10.1109/5.5972
  3. P. Maragos, 1987, Tutorial on Advances in Morphological Image Processing and Analysis, Optical Eng., Vol.26, No. 7, pp. 623-623.
  4. E. Fink and M. Heath, 2001, Image-Processing Projects for an Algorithms Course, Int. J. of Pattern Recognition and Artificial Intelligence, Vol. 15, Issue 5, pp. 859-868. https://doi.org/10.1142/S0218001401001192
  5. W. Frei and C. C. Chen, 1977, Fast Boundary Detection: A Generalization and a New Algorithm, IEEE Trans. Computers, Vol. C-26, No. 10, pp. 988-998. https://doi.org/10.1109/TC.1977.1674733
  6. A. Goshtasby. and H. L. Shyu, 1995, Edge Detection by Curve Fitting, Image and Vision Computing, Science Direct, Vol. 13, Issue 3, pp. 169-177.
  7. C. R. Pyo, S. M. Yang, S. H. Kang and S. M. Yoon, 2007, Development of Green-Sheet Measurement Algorithm by Image Processing Technique, Trans. Mater. Process, Vol. 16, No. 4, pp. 313-316. https://doi.org/10.5228/KSPP.2007.16.4.313