Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
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A Multiple Threshold Selection Algorithm Based on Maximum Fuzzy Entropy for the Final Inspection of Flip Chip BGA

플립 칩 BGA 최종 검사를 위한 최대퍼지엔트로피 기반의 다중임계값 선정 알고리즘

  • 김경범 (국립충주대학교 기계설계학과)
  • Published : 2004.04.01
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Abstract

Quality control is essential to the final product in BGA-type PCB fabrication. So, many automatic vision systems have been developed to achieve speedy, low cost and high quality inspection. A multiple threshold selection algorithm is a very important technique for machine vision based inspection. In this paper, an inspected image is modeled by using fuzzy sets and then the parameters of specified membership functions are estimated to be in maximum fuzzy entropy with the probability of the fuzzy sets, using the exhausted search method. Fuzzy c-partitions with the estimated parameters are automatically generated, and then multiple thresholds are selected as the crossover points of the fuzzy sets that form the estimated fuzzy partitions. Several experiments related to flip chip BGA images show that the proposed algorithm outperforms previous ones using both entropy and variance, and also can be successfully applied to AVI systems.

Keywords

References

  1. Lin, C. S. and Lue, L. W., 'An Image System for Fast Positioning and Accuracy Inspection of Ball Grid Array Boards,' Microelectronics Reliability, Vol. 41, pp. 119-128,2001 https://doi.org/10.1016/S0026-2714(00)00213-4
  2. Sahoo, P. K., Soltani, S. and Wong, A. K. C, 'A Survey of Thresholding Techniques,' Computer Vision Graphics Image Processing, Vol. 41, pp. 233-260, 1988 https://doi.org/10.1016/0734-189X(88)90022-9
  3. Glasbey, C. A., 'An Analysis of Histogram-Based Thresholding Algorithm,' CVGIP: Graphical Models and Image Processing, Vol. 55, pp. 532-537, 1993 https://doi.org/10.1006/cgip.1993.1040
  4. Synder, W., 'Optimal Thresholding - A New Approach,' Pattern Recognition Letters, Vol. 11, pp. 803-810, 1990 https://doi.org/10.1016/0167-8655(90)90034-Y
  5. Ostu, N., 'A Threshold Selection Method for Gray-level Histogram,' IEEE Transactions on System Man Cybernetics, Vol. 9, pp. 62-66, 1979 https://doi.org/10.1109/TSMC.1979.4310076
  6. Pun, T., 'Entropic Thresholding: A New Approach,' Computer Vision Graphics and Image Processing, Vol. 16, pp. 210-239, 1981 https://doi.org/10.1016/0146-664X(81)90038-1
  7. Kapur, J. N., Sahoo, P. K. and Wong, A. K. C, 'A New Method for gray Level Picture Thresholding Using the Entropy of the Histogram,' Computer Vision Graphics and Image Processing, Vol. 29, pp. 273-285,1985 https://doi.org/10.1016/0734-189X(85)90125-2
  8. Li, C. H. and Lee, C. K., 'Minimum Cross Entropy Thresholding,' Pattern Recognition, Vol. 26, pp. 617-625,1993 https://doi.org/10.1016/0031-3203(93)90115-D
  9. Kim, G. B. and Chung, S. C, 'Selection Method of Multiple Threshold Based on Probability Distribution Function Using Fuzzy Clustering,' Korean Society of Precision Engineering, Vol. 16, No. 5, pp. 48-57, 1999