Title :
Outdoor fire detection based on color and motion characteristics
Author :
Jamali, Mohsin ; Samavi, S. ; Nejati, M. ; Mirmahboub, B.
Author_Institution :
Dept. of Electr. & Comput. Eng., Isfahan Univ. of Technol., Isfahan, Iran
Abstract :
With due attention to industry deployment and extension of urban zones, early warning systems have critical role in giving emergency response to unexpected events. Video-base fire detection is a low cost and effective method for this purpose. Most of available fire detection methods only use color information in detection process that is inaccurate. This paper intends to increase the accuracy of fire detection in video sequences using motion detection and combination of two classifiers. Movement of pixels and their color in the YCbCr space are considered for detection. Using this combined method, false alarms due to movements of ordinary objects with fire-like color, are greatly reduced in comparison with other color based fire detection systems.
Keywords :
alarm systems; emergency services; fires; image classification; image colour analysis; image motion analysis; image sequences; support vector machines; video signal processing; SVM classification; YCbCr space; classifiers; color characteristics; color information; early warning systems; emergency response; false alarms; fire-like color; industry deployment; motion characteristics; motion detection; outdoor fire detection; pixel movement; urban zones; video sequences; Color; Fires; Image color analysis; Mathematical model; Motion detection; Support vector machines; Video sequences; Gaussian Mixture Models; YCbCr color space; fire detection; motion detection; support vector machines;
Conference_Titel :
Electrical Engineering (ICEE), 2013 21st Iranian Conference on
Conference_Location :
Mashhad
DOI :
10.1109/IranianCEE.2013.6599593