Cart (Loading....) | Create Account
Close category search window
 

Color context analysis based efficient real-time flame detection algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Huan Li ; Dept. of Comput. Sci., Dongguan Univ. of Technol., Dongguan ; Shan Chang ; Zhe Li ; Lipng Shao

In this study, we propose a novel color context analysis based efficient real-time flame detection algorithm (CCAFDA). To measure the relevance of color context of every two adjacent flames in flame image sequences, two new flame feature vectors are defined: one is the flame detection context based dynamic feature row vector and the other is the optimal flame feature area vector. The proposed algorithm uses the flame detection context based dynamic feature row vector and the optimal flame feature area vector as the joining point between every two adjacent flames and then according to the relationship of color context of multiple frames as well as the relevance between the adjacent pixels, selects the area of optimal flame feature in real time and adjusts the area of optimal flame feature dynamic. The proposed methods only scans the optimal flame feature area in each frame rather than scans every single pixel for each frame, and then uses the burning degree of the optimal flame feature area as a measurement to estimate the burning degree of the whole fire flames. To compare with the conventional method which scans the whole flame video through point by point scanning in RGB color space, the proposed methods improved the efficiency which can detect the flame status in video stream in real time. Experiments show the proposed algorithm improved the efficiency for detection and estimate of the boiler flame.

Published in:

Industrial Electronics and Applications, 2008. ICIEA 2008. 3rd IEEE Conference on

Date of Conference:

3-5 June 2008

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.