Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Robust Object Extraction Algorithm in the Sea Environment

해양환경에서 강건한 물표 추적 알고리즘

  • 박지원 (목포해양대학교 해양전자.통신.컴퓨터공학과) ;
  • 정종면 (목포해양대학교 해양컴퓨터공학과)
  • Received : 2014.03.09
  • Accepted : 2014.05.26
  • Published : 2014.06.25
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Abstract

In this paper, we proposed a robust object extraction and tracking algorithm in the IR image sequence acquired in the sea environment. In order to extract size-invariant object, we detect horizontal and vertical edges by using DWT and combine it to generate saliency map. To extract object region, binarization technique is applied to saliency map. The correspondences between objects in consecutive frames are defined by the calculating minimum weighted Euclidean distance as a matching measure. Finally, object trajectories are determined by considering false correspondences such as entering object, vanishing objects and false object and so on. The proposed algorithm can find trajectories robustly, which has shown by experimental results.

본 논문에서는 해양환경에서 취득한 열상 영상에서 물표를 강건하게 탐지하고 추적하는 알고리즘을 제안한다. 먼저 2-D 이산 Harr 웨이블렛 변환(DHWT) 기법을 이용하여 수평, 수직에지를 얻은 다음 수직 및 수평 에지들을 서로 곱하여 하나의 영상으로 결합해 돌출지도를 생성한다. 그런 다음 돌출지도를 이진화하여 물표를 추출한다. 물표를 추적하기 위하여 인접한 프레임에 존재하는 물체간의 가중치가 부여된 유클리디언 거리를 정합척도로 사용하였으며, 정합결과에 대해 물체의 나타남, 사라짐, 잘못된 물체 추출 등을 고려한 궤적관리를 통하여 최종적인 물체 궤적을 얻는다. 실험결과는 제안하는 알고리즘이 물체를 강건하게 추적함을 보인다.

Keywords

References

  1. Douglas Faulkener, Shipping Safety, Ingenia, 2003.
  2. European Maritime Safety Agency, Maritime Accident Review 2010, 2010.
  3. Helsinki Commission, Baltic Marine Environment Protection Commission, Report on Shipping Accidents in Baltic Sea Area during 2010, 2010, 2001-2010.
  4. Korean Maritime Safety Tribunal, Maritime accident review 2013, 2013.
  5. S. Gaarder, K. Rongstad, M. Olofsson, "Impact of Human Elements in Marine Risk Management", Guedes Soares C., Advances in safety and reliability, pp. 857-898, Pergamon, 1997.
  6. Alper Yilmaz, Omar Javed, Mubarak Shah, "Object Tracking: A Survey", ACM Computing Surveys, Vol. 38, Issue 4, Article No. 13, 2006.
  7. Virgil E. Vicker, "Plateau Equalization Algorithm for Real-time Display of High-quality Infrared Imagery", Optical engineering, Vol. 35, No. 7, pp. 1921-1926, July 1996. https://doi.org/10.1117/1.601006
  8. Qing-hua Chen et al, "An Efficient Approach To Extraction ROI From Infrared Image Sequence", Proc. of SPIE Advances in infrared imaging and application, Vol. 7383, 738345-1, coi:10.1117/12.835140, June 2009.
  9. Kjell Brunstrom et al, "Object Detection in Cluttered Infrared Images", Optical engineering, Vol. 42, No.2, pp. 388-399, Feb 2003. https://doi.org/10.1117/1.1531637
  10. Jongmyeon Jeong and G. Park, "Object Detection Method in Sea Environment using Fast Region Merge Algorithm," Journal of Korean Institute of Intelligent Systems, Vol. 22, pp. 610-616, 2012. https://doi.org/10.5391/JKIIS.2012.22.5.610
  11. David G. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints", International Journal of Computer Vision, Volume 60 Issue 2, pp. 91-110, 2004. https://doi.org/10.1023/B:VISI.0000029664.99615.94
  12. Herbert Bay, Tinne Tuytelaars, and Luc Van Gool, "Surf: Speeded Up Robust Features," European Conference on Computer Vision, Vol. 3951, pp. 404-417, 2006.
  13. Dorin Comaniciu, "Mean shift : a robust approach toward feature space analysis", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, No. 5, May 2002.
  14. Jongmyeon Jeong, Ki Tae Park and Gyei-Kark Park, "Robust Object Detection in Sea Environment Based on DWT", Soft Computing in Intelligent Control Advances in Intelligent Systems and Computing, Vol. 272, pp. 45-53, 2013.
  15. Jongmyeon Jeong and Young Shik Moon, "A Robust Algorithm for Tracking Feature Points with Incomplete Trajectories," Journal of the Institute of Electronics Engineers of Korea, Vol. 37, pp. 25-37, 2000.
  16. D.P Kottke, and Ying Sun, "Motion Estimation via Cluster Matching", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 16, No. 11, pp. 1128-1132, 1994. https://doi.org/10.1109/34.334394