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