By Topic

On approach to vision based fire detection based on type-2 fuzzy clustering

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)
Ha Dai Duong ; Dept. of Inf. Syst., Le Quy Don Tech. Univ., Hanoi, Vietnam ; Dinh Dung Nguyen ; Long Thanh Ngo ; Dao Thanh Tinh

During the last ten years computer vision techniques have shown a great potential in solving the problem of automatic fire detection. Vision-based fire detection offers many advantages over the conventional methods that use smoke and heat detectors. This paper presents a novel approach for fire detection by modeling the structure of spatial of fire, this structure is considered in terms of the color intensity of fire pixels. Furthers the type-2 fuzzy clustering technique is applied to separate fire-color pixels into some clusters, then these clusters are used to model structure of fire. Experimental results show that our method is capable of detecting fire in early state of fire and weak light-intensity environment; and this method uses only information on a single image so it can be integrated into the surveillance system that used dynamic camera.

Published in:

Soft Computing and Pattern Recognition (SoCPaR), 2011 International Conference of

Date of Conference:

14-16 Oct. 2011