DocumentCode :
588772
Title :
A Smoke Detection Algorithm Based on Discrete Wavelet Transform and Correlation Analysis
Author :
Wu Meng-Yu ; Han Ning ; Luo Qin-Juan
Author_Institution :
Sch. of Technol., Beijing Forestry Univ., Beijing, China
fYear :
2012
fDate :
2-4 Nov. 2012
Firstpage :
281
Lastpage :
284
Abstract :
A smoke detection algorithm based on Discrete Wavelet Transform and Correlation Analysis is presented to distinguish smoke and other smoke-like objects, especially cloud. Firstly, based on Gaussian mixture model, the target region of image is picked up. Secondly, we use Discrete Wavelet Transform to discriminate low frequency content and high frequency content of the images. At last, the high frequency information is analyzed by correlation. According to this algorithm, the motion region is smoke or not can be distinguished effectively and reliably. Experimental results show that the proposed method can improve the accuracy of smoke detection and reduce the false alarm.
Keywords :
Gaussian processes; correlation theory; discrete wavelet transforms; image motion analysis; object detection; smoke detectors; Gaussian mixture model; correlation analysis; discrete wavelet transform; frequency information analysis; image frequency content; image motion region; smoke detection algorithm; Correlation; Discrete wavelet transforms; Fires; Monitoring; Wavelet analysis; Discrete Wavelet Transform; cloud; correlation; forest fire smoke; target segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Information Networking and Security (MINES), 2012 Fourth International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-3093-0
Type :
conf
DOI :
10.1109/MINES.2012.46
Filename :
6405679
Link To Document :
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