Browse > Article

A Performance Analysis of Video Smoke Detection based on Back-Propagation Neural Network  

Im, Jae-Yoo (공주대학교 전기전자제어공학부)
Kim, Won-Ho (공주대학교 전기전자제어공학부)
Publication Information
Journal of Satellite, Information and Communications / v.9, no.4, 2014 , pp. 26-31 More about this Journal
Abstract
In this paper, we present performance analysis of video smoke detection based on BPN-Network that is using multi-smoke feature, and Neural Network. Conventional smoke detection method consist of simple or mixed functions using color, temporal, spatial characteristics. However, most of all, they don't consider the early fire conditions. In this paper, we analysis the smoke color and motion characteristics, and revised distinguish the candidate smoke region. Smoke diffusion, transparency and shape features are used for detection stage. Then it apply the BPN-Network (Back-Propagation Neural Network). The simulation results showed 91.31% accuracy and 2.62% of false detection rate.
Keywords
Video surveillance; smoke detection; Image processing; Neural network; Vision sensor;
Citations & Related Records
연도 인용수 순위
  • Reference
1 윤동열, 김성호, "무인헬기 및 센서네트워크 기반 화재 감시 시스템 설계", 퍼지 및 지능 시스템학회 논문지, Vol. 17, No. 2, pp. 173-178, April 2007.
2 Y. Rauste, "Forest Fire Detection with Satellites for Forest Fire Control" , Int'Archives of Photogrammetry and Remote Sensing, Vol. 31, Part B7, 1996
3 Yu Chunyu, Fang Jun, Wang Jinjun and Zhang Yongming, "Video Fire Smoke Detection Using Motion and Color Features", Fire Technology, Volume 46, Issue 3, 2010, pp 651-663.   DOI
4 Hidenori Maruta, Akihiro Nakamura and Fujio Kurokawa,"A New Approach for Smoke Detection with Texture Analysis and Support Vector Machine", Industrial Electronics (ISIE), July 2010.
5 "Wildfire Smoke Detection Using Computational Intelligence Techniques Enhanced With Synthetic Smoke Plume Generation" ,IEEE Transactions on systems, man, and cybernetics: Systems, Vol. 43, No. 4, July 2013.
6 R.Gonzalez-Gonzalez, V.Alarcon-Aquino, R.Rosas Romero, O.Starostenko, J.Rodriquez-Asomoza, "Wavelet-Based Smoke Detection in Outdoor Video Sequences" , Circuits and Systems (MWSCAS), August, 2010.
7 Ashish A. Narwade, Vrishali A. Chakkarwar, "Smoke Detection in video for early warning using static and dynamic features.", IJRET( International Journal of Research in Engineering and Technology) Vol. 02, No.11 November 2013.
8 Marin Bugaric, Toni jakovcevic, Darko Stipanicev, "Adaptive estimation of visual smoke detection parameters based on spatial data and fire risk index.", Computer Vision and Image Understanding, Vol.118, January 2014.
9 Tung Xuan Truong, Jong-Myon Kim, "Fire flame detection in video sequences using multi-stage pattern recognition techniques.", Engineering Applications of Artificial Intelligence, Vol.25, No.7, October 2012.