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Real-time Flame Detection Using Colour and Dynamic Features of Flame Based on FFmpeg

화염의 색상 및 동적 특성을 이용한 FFmpeg 기반 실시간 화염 검출

  • 김현태 (동의대학교 멀티미디어공학과)
  • Received : 2014.07.23
  • Accepted : 2014.09.19
  • Published : 2014.09.30

Abstract

In this paper, we propose a system which can detect the flame in real time from the high-quality IP camera. First, open directly the RTSP streams transmitted from the IP camera using the library FFmpeg as opening a video file. The second thing is to extract the background images from video signal using Gaussian mixture model. Then the foreground images are obtained through subtracting operation between the input image and the background image. Separated foreground image through a mathematical morphology operation are considered as candidate area. By analysing colour information and dynamic characteristics of the candidate area, flame is determined finally. Through the experiments with input videos from IP camera, the proposed algorithms were useful to detect flames.

본 논문에서는 고화질 IP 카메라로부터 입력되는 영상으로부터 실시간으로 화염을 검출할 수 있는 시스템을 제안한다. 먼저 FFmpeg 라이브러리를 이용하여 비디오 파일을 오픈하는 것처럼 IP 카메라로부터 전송되는 RTSP 스트림을 직접 오픈한다. 두 번째는 입력영상으로부터 혼합 가우시안 모델을 이용하여 배경영상을 추출한다. 그 다음에는 입력 영상과 배경영상간의 차신호로부터 전경영상을 구한다. 분리된 전경영상은 수학적 모폴로지 연산을 거쳐 후보영역으로 간주한다. 후보영역의 색정보와 화염의 동적 특성을 분석하여 최종적으로 화염을 검출한다. 실험 결과를 통하여 제안하는 방법이 화염을 검출하는 데 효과적인 것을 보인다.

Keywords

References

  1. G. Kim, J. Kim, H. Kim, J. Park, and Y. Yu, "Vehicle Tracking Using Euclidean Distance," J. of the Korea Institute of Electronic Communication Science, vol. 7, no. 6, 2012, pp. 1293-1299.
  2. H. Kim, G. Lee, J. park, and Y. Yu, "Vehicle Detection in Tunnel using Gaussian Mixture Model and Mathematical Morphological Processing," J. of the Korea Institute of Electronic Communication Science, vol. 7, no. 5, 2012, pp. 967-974.
  3. K. Park and H. Kim, "A Study for Video-based Vehicle Surveillance on Outdoor Road," J. of the Korea Institute of Electronic Communication Science, vol. 8, no. 11, 2013, pp. 1647-1653. https://doi.org/10.13067/JKIECS.2013.8.11.1647
  4. H. Kim and J. Park, "Smoke Detection in Outdoor Using Its Statistical Characteristics," J. of the Korea Institute of Electronic Communication Science, vol. 9, no. 2, 2014, pp. 149-154. https://doi.org/10.13067/JKIECS.2014.9.2.149
  5. G. Healey, D. Slater, T. Lin, B. Drda, and A. D. Goedeke, "A System for Real-time Fire Detection," Proc. on IEEE Computer Vision and Pattern Recognition Conf. (CVPR93), New York, June 1993, pp. 605-606.
  6. B. U. Toreyin, Y. Dedeoglu, U. Gudukbay, and A. E. Cetin, "Computer vision based method for real-time and flame detection," Pattern Recognition Letters, Elsevier, vol. 27, issue 1, 2006, pp. 49-58. https://doi.org/10.1016/j.patrec.2005.06.015
  7. J. Jung, J. Kim, D. Kim, S. Kwon, J. Lee, S. Ju, H. Im, N. Jung, C. Park, and K. Ryu, "Design and implementation of smart multimedia editor system based on education cloud services system," Proc. on Human and Computer Interface Conf. (HCI2014), Gangwon Province, Korea, Feb. 2014, pp. 913-916.