Fire Detecting System Design under the Mainframe Computer Vision

Ming Yi Yu

doi:10.4028/www.scientific.net/AMM.602-605.2038

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 602-605Fire Detecting System Design under the Mainframe...

Fire Detecting System Design under the Mainframe Computer Vision

Abstract:

This paper focused on the fire detecting problem. Traditionally, fire was detected based on the frame difference by subtracting the image pixel. When there existed background similar to its flame color and shape in the environment where the fire happened,, the result of frame difference subtracting is not obvious and the algorithm cannot detect the fire problem according to the result. This paper put forward a fire detecting method based on support vector basis algorithm. The experiment indicated that this kind of neural network model achieved precise fire detecting under the background similar to itself, efficiently decreased the detecting error rate, and obtained satisfactory results.

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Periodical:

Applied Mechanics and Materials (Volumes 602-605)

Pages:

2038-2040

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.602-605.2038

Citation:

Cite this paper

Online since:

August 2014

Authors:

Ming Yi Yu*

Keywords:

Computer Vision, Fire Detecting, Neural Network (NN)

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* - Corresponding Author

References

[1] B.U. Toreyin,Y. Dedeoglu,U. Gudukbay A.E. Cetin, Computer vision based method for real-time fire and flame detection[J]. Short Communication Pattern Recognition Letters, 2006, 27(1): 49-58.

DOI: 10.1016/j.patrec.2005.06.015

Google Scholar

[2] Turgay C, Deminel H , Ozkaramanli H, et a l. , Fire detection n using statist ical co lo r mo del in v ideo sequences [J]. Journal of Visual Communication and Image Representation, 2007, 18( 2) : 176-185.

DOI: 10.1016/j.jvcir.2006.12.003

Google Scholar

[3] Chen X J，Li Y，Harrison R，et al． Type-2 fuzzy logic based classifier fusion for support vector machines[J]. Applied Soft Computing，2008，8( 3) : 1222-1231.

DOI: 10.1016/j.asoc.2007.02.019

Google Scholar

[4] Power P W, Schoonees J A. Understanding background mixture models for foregrounds segmentation [C]. Proceedings of Image and Vision Computing, 2002: 267-271.

Google Scholar

[5] Lowe D C. Distinctive image features from scale-invariantkeypoints[J]. International Journal Computer Vision, 2004, 60(2): 91一110.

DOI: 10.1023/b:visi.0000029664.99615.94

Google Scholar