Adaptive flame detection using randomness testing and robust features

Title
Adaptive flame detection using randomness testing and robust features
Authors
김학일
Keywords
Flame detection Randomness test Flame colorprobability Motion probability Convolution
Issue Date
2013
Publisher
FIRE SAFETY JOURNAL
Series/Report no.
FIRE SAFETY JOURNAL ; Vol55 Startpage 116 Endpage 125
Abstract
This paper presents a novel approach to detect flame based on robust features and randomness testing. The flame color probability is estimated based on a Gaussian model learned in the YCbCr color space. The motion probability is then obtained by employing the background image updated dynamically with an approximate median method. The color and motion probabilities are integrated in order to obtain flame candidates, from which a feature vector comprised of seven features is extracted for each frame. The successive feature vectors are then applied to the Wald?Wolfowitz randomness test in order to obtain the prior flame probability. Finally, the convolution is defined in order to update the prior probability into a posterior probability for improving the system reliability, and an alarm level is determined based on the posterior probability. The presented method was successfully applied to real- environmen tintelligent surveillance systems and proved to be effective, robust, and adaptive, irrespective of the environment, weather conditions, or video quality.
URI
http://dx.doi.org/10.1016/j.firesaf.2012.10.011
http://dspace.inha.ac.kr/handle/10505/33446
ISSN
0379-7112
Appears in Collections:
College of Engineering(공과대학) > Information and Communication Engineering (정보통신공학) > Journal Papers, Reports(정보통신공학 논문, 보고서)
Files in This Item:
35591.pdfDownload

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse