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Reseach Article

Optimized Flame Detection

by Abhilash Nunes, Leroy Dias, Shalem Pereira, Meena Ugale
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 113 - Number 15
Year of Publication: 2015
Authors: Abhilash Nunes, Leroy Dias, Shalem Pereira, Meena Ugale
10.5120/19905-2032

Abhilash Nunes, Leroy Dias, Shalem Pereira, Meena Ugale . Optimized Flame Detection. International Journal of Computer Applications. 113, 15 ( March 2015), 41-44. DOI=10.5120/19905-2032

@article{ 10.5120/19905-2032,
author = { Abhilash Nunes, Leroy Dias, Shalem Pereira, Meena Ugale },
title = { Optimized Flame Detection },
journal = { International Journal of Computer Applications },
issue_date = { March 2015 },
volume = { 113 },
number = { 15 },
month = { March },
year = { 2015 },
issn = { 0975-8887 },
pages = { 41-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume113/number15/19905-2032/ },
doi = { 10.5120/19905-2032 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:51:03.011976+05:30
%A Abhilash Nunes
%A Leroy Dias
%A Shalem Pereira
%A Meena Ugale
%T Optimized Flame Detection
%J International Journal of Computer Applications
%@ 0975-8887
%V 113
%N 15
%P 41-44
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, the system focuses on optimizing the flame detection by identifying gray cycle pixels nearby the flame, which is generated because of smoke and of spreading of fire pixel and the area spread of flame. The model uses fuzzy logic or fuzzy inference system (FIS) to detect fire pixels. These techniques can be used to reduce false alarm by giving the accurate result of fire occurrence along with fire detection methods. The system also give the opportunity to adjust the system by applying different combination of fire detecting techniques which will help in implementation of system according to different sensitive area requirement.

References
  1. TurgayÇelik, HüseyinÖzkaramanl? and HasanDemirel, "Fire and Smoke Detection without Sensors: Image Processing Based Approach", 15th European Signal Processing Conference (EUSIPCO 2007), Poznan, Poland, September-3-7, 2007.
  2. GauravYadav,Vikas Gupta, Vinod Gaur and Dr. MahuaBhattacharya, "Optimized Flame Detection Using Image Processing Based Techniques", ISSN: 0976-5166, Vol. 3 No. 2, April-May, 2012.
  3. VipinVenu, "Image Processing Based Forest Fire Detection", ISSN 2250-2459, Volume 2, Issue 2, February 2012.
  4. Chen, T. , Wu, P. , Chiou, Y. , "An early fire-detection method based on image processing", Proc. IEEE Internat. Conf. on Image Processing, ICIP'04, pp. 1707-1710, 2004.
  5. Klir, G. J. , Yuan B. , "Fuzzy Sets and Fuzzy Logic", Prentice Hall, 1995.
  6. Mathews, J. H. , Fink, K. D. , "Numerical Methods using matlab", Prentice Hall, 1999.
  7. Turgay Celik, Huseyin Ozkaramanli, Hasan Demirel, "Fire Pixel Classification Using Fuzzy Logic and Statistical Color Model", ICASSP 2007.
  8. T. Chen, P. Wu, and Y. Chiou (2004): "An early fire-detection method based on image processing", in ICIP '04, pp. 1707–1710.
  9. C. -B. Liu, N. Ahuja (2004): "Vision based fire detection", Proceedings of the 17th International Conference on Pattern Recognition (ICPR' 04), Vol. 4, pp. 134-137.
  10. S. Noda, K. Ueda (1994): "Fire detection in tunnels using an image processing method", in Vehicle Navigation & Information Systems Conference Proceedings, pp. 57-62.
  11. TurgayCelik (2010): "Fast and Efficient Method for Fire Detection Using Image Processing", ETRI Journal, Volume 32, Number 6.
Index Terms

Computer Science
Information Sciences

Keywords

Fire detection Fuzzy Inference System(FIS) Mamdani model RGB YCbCr.