Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
권호 표지
DOI QR코드

DOI QR Code

Development of Pipe Fault Inspection System using Computer Vision

컴퓨터 비젼을 이용한 파이프 불량 검사시스템 개발

  • 박찬호 ((주)티엠디바이스 연구소) ;
  • 양순용 (울산대학교 기계자동차공학부) ;
  • 안경관 (울산대학교 기계자동차공학부) ;
  • 오현옥 (부국산업주식회사 연구소) ;
  • 이병룡 (울산대학교 기계자동차공학부)
  • Published : 2003.10.01
Download PDF
⟨ Previous Next ⟩

Abstract

A computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and the radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation is introduced for line detection. The dimension of inner and outer radius of pipe is calculated by the proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle, by which pipes with wrong end-shape can be classified and removed.

Keywords

References

  1. H. Maitre, 'Contribution to the prediction of performance of the hough transform', IEEE Trans. on Pattern Anal. And Machine Intel, PAMI-8(5), 1986
  2. J. Illingworth and J. Kittler, 'A survey of the hough transform', comput. vision graphics image processl., vol. 44, pp.87-116, 1988 https://doi.org/10.1016/S0734-189X(88)80033-1
  3. J. L. Turney, T. N. Mudge, and R. A. Volz, 'Recognizing partially occluded parts', IEEE Trans, on Pattern Anal. And Machine Intel, PAMI-7(4), pp.410-421, 1985 https://doi.org/10.1109/TPAMI.1985.4767680
  4. G. Stockman, S. Kopstein and S. Benett, 'Matching images to models for registration and object dection via clustering', IEEE Trans, on Pattern Anal. And Machine Intel, PAMI-4, pp.229-241,1982 https://doi.org/10.1109/TPAMI.1982.4767240
  5. B. Bhanu and O. D. Faugeras, 'Shape matching pf. two-dimensional objects', IEEE Trans. on Pattern Anal. And Machine Intel, PAMI-6(2),pp.l37-155,1986
  6. C. K.Chan and M. B. Sandler, 'A complete shape recognition system using the hough transform and neural network', IAPR, 11th, pp.21-24.1992 https://doi.org/10.1109/ICPR.1992.201713
  7. D. H. Ballard, 'Generalizing hough transform to detect arbitrary shapes', Pattern Recognition., vol. 13, pp.111-122,1981 https://doi.org/10.1016/0031-3203(81)90009-1
  8. C. Kimme, D. H. Ballard and J. Sklansky, 'Finding circles by an array of accumulators', Comm. Of ACM., vol. 18, pp.111-122, 1981 https://doi.org/10.1145/360666.360677
  9. M. W. Koch and R. L. Kashyap, 'Using polygons to recognition and locate partially occluded objects', IEEE Trans. on Pattern Anal. And Machine Intel, PAMI-9(4), 1987
  10. W.-Y. Wu and J. W. M.-J., 'Elliptical ob jection by using its geometric properties', Pattern Recognition., vol. 26(10), pp.1499-1509,1993 https://doi.org/10.1016/0031-3203(93)90155-P
  11. P. V. C, Hough, 'Method and means for recognizing complex patterns', U.S. Patent, 3,069,654, Dec. 18,1962
  12. R. O. Duda and P. E. Hart, 'Use of the hough transformation to detect lines and curves in picture', Comm. Of ACM., vol. 15, no. l,Janu.,pp.ll-15,1972 https://doi.org/10.1145/361237.361242
  13. 조강현, 유범재 공역, '3차원 비젼', 대영사, 2000