Fire Detection Technologies Based on Video Image

Article Preview

Abstract:

Because of high fire frequency and huge losses, the research of fire signal detection in the monitoring system is an important task in the fire-preventing field. The fire signal detection method based on vision can overcome the shortcomings that exist in some traditional methods i.e. it can surmount the large impact on environmental interference factors, such as temperature, photographic and smoke of environment. With many researcher’s results, it shows clearly that the error rate of flame recognition is low, and also the real-time ability and the anti-disturbance ability are very good.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

134-138

Citation:

Online since:

January 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Treyin, B.U., Dedeoglu, Y., Güdükbay, U., cetin, A.E., Computer vision based method for real-time fire and flame detection, Pattern Recogn. Lett. 27(1), 49–58 (2006).

DOI: 10.1016/j.patrec.2005.06.015

Google Scholar

[2] Treyin, B.U., cetin, A.E., Online detection of fire in video, In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), p.1–5 (2007).

Google Scholar

[3] Yusuf Hakan Habiboglu, Osman Günay. Cetin, A. E, Covariance matrix-based fire and flame detection method in video, Machine Vision and Applications, DOI 10. 1007/s00138-011-0369-1(2011).

DOI: 10.1007/s00138-011-0369-1

Google Scholar

[4] Lin Shi, Zhe Cao, The flame detection and background interference filtering algorithm based on video image, Computer Science and Information Engineering 2009 WRI World Congress, 6, 559-563( 2009).

DOI: 10.1109/csie.2009.138

Google Scholar

[5] Horng W B, Peng J W, Image-based fire detection using neural networks, Proceedings of the Joint Conference on Information Sciences(JCIS), Kaohsiung, Taiwan,2006.

DOI: 10.2991/jcis.2006.301

Google Scholar

[6] Huang P H, Su J Y, Lu Z M, et al. A fire-alarming method based on video processing, International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp.359-364(2006).

DOI: 10.1109/iih-msp.2006.265017

Google Scholar

[7] Chen Juan, He Yaping, Wang Jian. Multi-feature fusion based fast video flame detection. Building and Environment, 45: 1113-1122(2010).

DOI: 10.1016/j.buildenv.2009.10.017

Google Scholar

[8] Liu Peixun, All-weather fire detection system based on video surveillance, Master degree thesis, Jilin University, (2011).

Google Scholar

[9] Zhou Junying, Du Xiaoxiao. Image recognition technology in fire detection, Fire Science and Technology, 26(4), 417-420(2007).

Google Scholar

[10] ZhangJinHua, ZhuangJian, DuHaiFeng, WangSunan, A flame recognition algorithm based on multi-feature fusion in video, xi 'an jiaotong university, 40 (7), 811-814.

Google Scholar

[11] Xiong Z, Caballero R, Wang H, Alan MF, Muhidin AL, Peng P-Y, Video-based smoke detection: possibilities, techniques, and challenges, In: IFPA, fire suppression and detection research and applications-a technical working conference (SUPDET), Orlando, FL (2007).

Google Scholar

[12] Yuan F, A fast accumulative motion orientation model based on integral image for video smoke detection, Pattern Recog Lett, 29(7), 925–932 (2008).

DOI: 10.1016/j.patrec.2008.01.013

Google Scholar

[13] Cui Y, Dong H, Zhou E. An early fire detection method based on smoke texture analysis and discrimination, In: Proceedings of the 2008 congress on image and signal processing, 3(8), 95–99 (2008).

DOI: 10.1109/cisp.2008.397

Google Scholar

[14] Yu Chunyu, Fang Jun, Wang Jinjun, Zhang Yongming, Video fire smoke detection using motion and color features, Fire technology, 46, 651–663(2010).

DOI: 10.1007/s10694-009-0110-z

Google Scholar

[15] Turgay elik, Hüseyin zkaramanl, Hasan Demirel, Fire and smoke detection without sensors: image processing based approach, 15th European Signal Processing Conference , 1794-1798(2007).

Google Scholar

[16] Turgay Celik, Huseyin Ozkaramanli, Hasan Demirel, FIRE PIXEL CLASSIFICATION USING FUZZY LOGIC AND STATISTICAL COLOR MODEL, ICASSP (2007).

DOI: 10.1109/icassp.2007.366130

Google Scholar

[17] Turgay Celik, Hasan Demirel, Huseyin Ozkaramanli, Mustafa Uyguroglu, Fire Detection Using Staistical Color Model in Video Sequences, Journal of Visual Communication and Image Representation , doi: 10. 1016/j. jvcir. 2006. 12. 003(2007).

DOI: 10.1016/j.jvcir.2006.12.003

Google Scholar

[18] H. J. Grech-Cini, Smoke Detection, US Patent No. US6844818B2.

Google Scholar

[19] Wei Yingzhuo, Zhang Shaowu, Liu Yanwei, Smoke detection based on multi-spectral images, Spectroscopy and Spectral Analysis, 30 (4), 1061-1064(2010).

Google Scholar

[20] Yuan Feiniu, Zhang Yongming, Liu Shixing, Yu Chunyu, Shen Shilin, Video smoke detection based on the accumulation and the main direction of motion, Image and Graphics, 4, 808-813(2008).

Google Scholar

[21] Xiong Z, Caballero R, Wang H, Finn A M, Lelie M A, Peng P-Y, Video- Based Smoke Detection: Possibilities, Techniques and Challenges, Proc. Suppression and Detection Research and Applications, p.112(2007).

Google Scholar