The Journal of Korean Institute of Information Technology (한국정보기술학회논문지)

Korean Institute of Information Technology (한국정보기술학회)
권호 표지
DOI QR코드

DOI QR Code

Real-time Rebar Injection Endpoints Tracking Method to Improve the Straightness of Rebars

철근 직진도 개선을 위한 실시간 철근 사출 끝점 추적 방법

  • Received : 2019.04.10
  • Accepted : 2019.07.21
  • Published : 2019.08.01
⟨ Previous Next ⟩

Abstract

In this paper, we propose a method that can detect and trace the end point of real - time reinforcement steel to various environmental conditions of industrial field by using Median flow and Depth information. We proposed a method to derive two steel end points by using Median filter, Binarization, Morphology, and Blob algorithm on image depth information. The coordinates of the final position were determined by comparing the coordinates of the reinforcement steel endpoints detected in the Depth image and the position tracking coordinates of the reinforcement steel using Median Flow. As a result, when the existing Median Flow method was used, the success rate of the final position determination of reinforcement steel of 75% was increased to 95% when the Depth of reinforcement steel was used.

본 논문에서는 Median flow와 영상의 Depth 정보를 이용하여 산업 현장의 다양한 환경 조건에서 실시간 철근의 끝점 추적 및 검출이 가능한 방법을 제안한다. 영상의 Depth 정보에 Median filter, Binarization, Morphology, Blob의 알고리즘을 사용하여 2개의 철근 끝점을 검출하는 방법을 제안하였다. 실시간 철근 끝점 추적을 위해서는 Median flow의 알고리즘을 이용하여 철근의 움직임 방향과 위치 추적을 제안하였다. 그리고 Depth 영상에서 검출된 철근 끝점 좌표와 Median flow를 이용한 철근의 위치추적 좌표를 서로 비교하여 최종 위치 좌표를 결정하였다. 그 결과 기존 Median flow 방식만 적용하였을 때 75% 정도의 철근의 최종 위치 판단 성공률이 Depth의 철근 끝점 정보까지 활용하였을 때는 95%까지 추적 성공률이 높아졌다.

Keywords

References

  1. Dae-il Kim, Jin-Sup Shin and Dae-Seong Kang, "A Study on Moving Object Tracking Algorithm Using FFPD and Depth Information", Journal of KIIT, Vol. 10, No. 12, pp. 167-172, Dec. 2012.
  2. Sang-Beom Lee and Yo-Sung Ho, "Real-time Eye Contact System Using a Kinect Depth Camera for Realistic Telepresence", The Journal of Korean Institute of Communications and Information Sciences, Vol. 37, No. 4, pp. 277-282 , Apr. 2012. https://doi.org/10.7840/KICS.2012.37C.4.277
  3. Innho Jee, "A Study on the Generation and Processing of Depth Map for Multi-resolution Image Using Belief Propagation Algorithm", The Journal of IIBC, Vol. 15, No. 6, pp. 201-208, Dec. 2015.
  4. Sung-Min Kim, Ju-Hwan Lee, Seung-Gyu Roh, and Sung-Yun Park, "The Study of Pre-processing Algorithm for Improving Efficiency of Optical Flow Method on Ultrasound Image", Journal of the Institute of Electronics Engineers of Korea. SC, Vol. 47, No. 5, pp. 24-32, Sep. 2010.
  5. Hyun-ji Cho and Doohee Nam, "Enhanced image detail control using Multi Channel Unsharp Mask Technique", The Journal of IIBC, Vol. 15, No. 1, pp. 165-170, Feb. 2015
  6. Sung-Min Kim, Ju-Hwan Lee, Seung-Gyu Roh, and Sung-Yun Park, "The Study of Pre-processing Algorithm for Improving Efficiency of Optical Flow Method on Ultrasound Image", Journal of the Institute of Electronics Engineers of Korea. SC, Vol. 47, No. 5, pp. 24-32, Sep. 2010.
  7. Z. Kalal, K. Mikolajczyk, and J Matas, "Forward-Backward Error: Automatic Detection of Tracking Failures", International conference on pattern recognition, Vol. 20, No. 4, pp. 2756- 29759, Aug. 2010.
  8. Z. Kalal, K. Mikolajczyk, and J Matas, "Tracking-Learning-Detection", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 34, No. 7, pp. 1409-1422 Jul. 2012. https://doi.org/10.1109/TPAMI.2011.239
  9. Sangpil Han, Min-jae Kim, Seokmok Park, and Joonki Paik, "Key-point Selection Method for Robust Object Tracking Based on Median Flow", Autumn Annual Conference of IEIE, Seoul, South Korea, pp. 370-372, Nov. 2016.
  10. S. Esakkirajan, T. Veerakumar, Adabala N. Subramanyam, and C. H. PremChand, "Removal of High Density Salt and Pepper Noise Through Modified Decision Based Unsymmetric Trimmed Median Filter", IEEE Signal Processing Letters, Vol. 18, No. 5, pp. 287-290, May 2011. https://doi.org/10.1109/LSP.2011.2122333
  11. Mohamed Roushd, "Comparative Study of Edge Detection Algorithms Applying on theGrayscale Noisy Image Using Morphological Filter", In GVIP Journal, Vol. 6, No. 4, pp. 17-23, Dec. 2006.
  12. Robert T. Collin, "Mean-shift Blob Tracking through Scale Space", In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'03), pp. 1-7. Jun. 2003.
  13. "Kanade-Lucas-Tomasi feature tracker", https://en.wikipedia.org/wiki/Kanade%E2%80%93Lucas%E2%80%93Tomasi_feature_tracker, [accessed: Feb. 2019]

Cited by

  1. An Algorithm for the Determination of Twisted Rebar using Feature Matching vol.19, pp.2, 2019, https://doi.org/10.14801/jkiit.2021.19.2.21