Journal of Advanced Navigation Technology (한국항행학회논문지)

The Korean Navigation Institute (한국항행학회)
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Development and Performance Evaluation of an Image Detection System for Efficient 4D Images

효율적인 4D 영상을 위한 영상 검출 시스템 개발 및 성능평가

  • Cho, Kyoung-Woo (Department of Information Technology Engineering, Korea University of Technology and Education) ;
  • Liu, Ze-Qi (Department of Information Technology Engineering, Korea University of Technology and Education) ;
  • Jeon, Min-Ho (Department of Information Technology Engineering, Korea University of Technology and Education) ;
  • Oh, Chang-Heon (Department of Information Technology Engineering, Korea University of Technology and Education)
  • Received : 2013.10.31
  • Accepted : 2013.12.30
  • Published : 2013.12.30
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Abstract

4D film is just a film that made by adding some physical effects to 3D film or general film. In order to provide physical effects to the audience, the data that make the physical effect must be added to each frames. In this paper, we proposed a video detection system that can efficiently provide physical effects by assessing the present situation such as explosion scene, snowing scene. The proposed video detection system contains an algorithm for fire detection by using R color and $C_r$ value, and also an algorithm for snow detection by using RGB color model. The system constitutes in a MCU that from 8051 family. In the performance evaluations, the result shows that 91% of detection rate in case of fire and 25% of false detection rate in case of snow. Also the system is capable of providing physical effects automatically.

4D 영화는 3D 혹은 일반영상과 함께 물리적인 효과를 추가한 영화이다. 시청자에게 물리적 효과를 제공하기 위해선 각 장면마다 적용할 물리 효과 데이터를 작성해야 한다. 본 논문에서는 영화의 폭발 장면이나 빙설, 적설 장면의 상황을 판단하여 효율적으로 물리효과를 제공할 수 있는 영상 검출 시스템을 제안한다. 제안하는 영상 검출 시스템은 R컬러와 적색차 정보인 $C_r$값을 이용한 화염 검출 알고리즘과 RGB 컬러를 이용한 적설 영역 검출 알고리즘, 8051 계열의 MCU를 사용한 제어시스템으로 구성된다. 성능평가 결과 화염의 경우 91%의 검출율을 보였으며, 적설 영역의 경우 26%의 오검출이 발생하였다. 또한 해당 알고리즘을 통한 자동적인 물리적 효과 제공이 가능함을 보였다.

Keywords

References

  1. Korea Creative Contents Agency, "Status and Prospects of Experiential(4D) technology and content", Culture and technology(CT) reports, no. 1, June 2010.
  2. J. S. Park, H. T. Kim, Y. S. Yu, "Video Based Fire Detection Algorithm using Gaussian Mixture Model", The Journal of The Korea institute of electronic communication sciences, vol. 6, no. 2, pp 206-211, April 2011.
  3. G. Healey, D. Slater, T. Lin, B. Drda, and A.. D. Goedeke, "A system for real-time fire detection", IEEE Computer Vision and Pattern Recognition, Proceedings CVPR '93, pp. 605-606, 1993.
  4. B. U. Toreyin, Y. Dedeoglu, U. Gudukbay, and A. E. Cetin, "Computer vision based method for real-time fire and flame detection", Pattern Recognition Letters, Volume 27, pp. 49-58, Jan. 2006. https://doi.org/10.1016/j.patrec.2005.06.015
  5. J. W. Jung, G. C. Park, S. S. Kim, Multimedia Communication for The Ubiquitous Age, Scitech media, 2006.
  6. Radio Communication Sector of ITU(ITU-R), "Recommendation ITU-R BT.601-7", Mar. 2011.
  7. H. S. Lee, W. H. Kim, "The Flame Color Analysis of Color Models for Fire Detection", The Journal of The Korea society of space technology, vol. 8, no. 3, pp. 52-57, Sep. 2013.
  8. D. H. Lee, J. W. Yoo, K. H. Lee, Y. Kim, "A Real Time Flame and Smoke Detection Algorithm Based on Conditional Test in $YC_bC_r$ Color Model and Adaptive Differential Image", Journal of the Korea society of computer and information, vol.15, no. 5, pp. 57-65, May 2010. https://doi.org/10.9708/jksci.2010.15.5.057
  9. JJ Koenderink and WA Richards, "Why is snow so bright?", JOSA A, vol. 9, issue 5, pp. 643-648, 1992. https://doi.org/10.1364/JOSAA.9.000643
  10. K. W. Cho, K. C. Wang, C. H. Oh, "A Study of Fire Detection Algorithm for Efficient 4D System", The Conference of The Korea institute of information and communication engineering, vol. 17, no. 2, Oct. 2013.