Journal of the Institute of Convergence Signal Processing (융합신호처리학회논문지)

The Korea Institute of Convergence Signal Processing (한국융합신호처리학회)
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Welding Bead Segmentation Algorithm Using Edge Enhancement and Active Contour

에지 향상과 활성 윤곽선을 이용한 용접 비드 영역화 알고리즘

  • Mlyahilu, John N. (Department of IT Convergence and Application Engineering, Pukyong National University) ;
  • Kim, Jong-Nam (Department of IT Convergence and Application Engineering, Pukyong National University)
  • Received : 2020.12.22
  • Accepted : 2020.12.31
  • Published : 2020.12.31
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Abstract

In this paper, we propose an algorithm for segmenting weld bead images using edge enhancement and active contours. In the proposed method, high-frequency filtering and contrast improvement are performed for edge enhancement, and then, by applying the active contour method, only the weld bead region can be obtained. The proposed algorithm detects an edge through high-frequency filtering and reinforces the detected edge by using contrast enhancement. After the edge information is improved in this way, the weld bead area can be extracted by applying the active contour method. The proposed algorithm shows better performance than the existing methods for segmenting the weld bead in the image. For the objective reliability of the proposed algorithm, it was compared with the existing high pass filtering methods, and it was confirmed that the welding bead segmentation of the proposed method is excellent. The proposed method can be usefully used in evaluating the quality of the weld bead through an additional procedure for the segmented weld bead.

본 논문에서는 에지 향상과 활성 윤곽선을 이용한 용접 비드 영상의 영역화 알고리즘을 제안한다. 제안 방법에서는 에지 향상을 위하여 고주파 필터링과 대비개선을 수행하며, 이후 활성 윤곽선 방법을 적용하면 용접비드만의 영역을 얻을 수 있다. 제안된 알고리즘은 고주파 필터링을 통하여 에지를 검출하며, 대비 개선을 이용하여 검출된 에지를 강화한다. 이렇게 에지 정보를 향상시킨 후에 활성 윤곽선 방법을 적용하여 용접비드 영역을 추출할 수 있다. 제안 알고리즘은 용접 비드 영역화를 위한 기존의 방법들 보다 우수한 성능을 보였다. 제안된 알고리즘의 객관적 신뢰성을 위해 기존의 다양한 고주파 필터링 방법들과 비교하여 용접 비드 영역화가 우수함을 확인하였다. 제안된 방법은 영역화된 용접 비드에 대해 추가적인 절차를 통하여 용접 비드의 품질 평가를 하는데 있어 유용하게 사용될 수 있을 것이다.

Keywords

Acknowledgement

본 논문은 과학기술정보통신부 지역SW서비스 사업화 지원 과제 및 중기청 창업성장 기술개발 사업의 지원으로 수행된 것임.

References

  1. O. Haffner, E. Kucera, and S. Kozak, "Weld Segmentation for Diagnostic and Evaluation Method," Cybernetics & Informatics, Levoca, Slovakia, pp. 1-6, 2016.
  2. O. Haffner, E. Kucera, and S Kozak, "Application of Pattern Recognition for a Welding Process," Communication Papers of the Federated Conference on Computer Science and Information Systems, 13, pp. 3-8, 2017.
  3. O. Haffner, E. Kucera, and P, Drahos, "Using Entropy for Welds Segmentation and Evaluation," Entropy, Vol. 21, No. 12, pp. 1-29, 2019.
  4. M. Kass, A. Witkin, and D. Terzopoulos, "Snakes: Active Contour Models," International Journal of Computer Vision, Vol. 1, No. 4, pp. 321- 331, 1988. https://doi.org/10.1007/BF00133570
  5. L.D. Cohen, "On active contour models and balloons," CVGIP: Image Understanding, Vol. 53, No. 2, pp. 211-218, 1991. https://doi.org/10.1016/1049-9660(91)90028-n
  6. D. Baswaraj, A. Govardhan, and P. Premchand, "Active Contours and Image Segmentation: The Current State of the Art," Global Journal of Computer Science and Technology Graphics and Vision, Vol. 12, No. 11, pp. 1-12, 2012.
  7. A. Mahmoudi, and F. Regragui, "Welding Defect Detection by Segmentation of Radiographic Images," WRI World Congress on Computer Science and Information Engineering, Los Angeles, CA, pp. 111-115, 2009.
  8. N. Awang, M. Fauadi, Z, Abdullah, S. Akmal, N.I. Anuar, A.Z.M Noor, S.A. Idris and M.H. Nordin,"Classification of Weld Bead Defects Based on Image Segmentation Method," Journal of Advanced Manufacturing Technology, Vol, 2, No. 4, pp. 51-06, 2018.
  9. A. Makandar, and B. Halalli, "Image Enhancement Techniques Using Highpass and Lowpass Filters," International Journal of Computer Applications, Vol. 109, No. 14, pp. 21-27, 2015. https://doi.org/10.5120/19256-0999
  10. A. Dogra and P. Bhalla, "Image Sharpening By Gaussian and Butterworth High Pass Filter," Biomedical and Pharmacology Journal, Vol. 7, No, 2, pp. 1-13, 2014. https://doi.org/10.13005/bpj/445
  11. R.J. Hemalatha, T.R. Thamizhvani, A.J.A Dhivya, J.E. Joseph, B. Babu and R. Chandasekaran, "Active Contour Based Segmentation Techniques for medical Image Analysis," Medical and Biological Image Analysis, pp. 17-34, 2018.