Browse > Article
http://dx.doi.org/10.3745/KIPSTB.2007.14-B.5.361

Smoke Detection using Block-based Difference Images and Projections  

Kim, Dong-Keun (공주대학교 컴퓨터공학부)
Kim, Won-Ho (공주대학교 전기전자공학부)
Publication Information
The KIPS Transactions:PartB / v.14B, no.5, 2007 , pp. 361-368 More about this Journal
Abstract
In this paper, we propose a smoke detection method which is based on block-wise difference of image frames in video. Our proposed method is composed of three steps which are (a) the detection step of the changed regions against the background, (b) the background update step, and (c) the smoke determination step from the changed regions. We first construct the block mean Image of frames in video. And to extract the changed regions against the background, we use a block-wise difference between background's block mean image and a current input frame's block mean image. After applying projections in block-based difference images, we can determine the changed regions as rectangles using projections of difference images. we propose a update scheme of background's block mean image using the projections. We decide the smoke region using the femoral statistics of the central position and YUV color in the changed region.
Keywords
Smoke Detection; Block-based difference image; Projection Profile;
Citations & Related Records
연도 인용수 순위
  • Reference
1 산림청, 2006년 간추린 통계, http://www.foa.go.kr
2 W. Phillips III et al, 'Frame Recognition in Video,' In Fifth IEEE Workshop on Applications of Computer Vision, pp.224-229, Dec. 2000
3 Che- Bin Liu and N. Ahuja, 'Vision based Fire Detection,' IEEE International Conference on Pattern Recognition, Cambridge, UK, August 2004   DOI
4 B. U. Toreyin et al, 'Wavelet based real-time smoke detection in video,' Signal Processing:Image Communication, EURASIP, Elsevier, vol. 20, pp. 255-26, 2005   DOI   ScienceOn
5 F. G. Rodriguez et al, 'Smoke Monitoring and measurement Using Image Processing. Application to Forest Fires,' Automatic Target Recognition XIII, Proceedings of SPIE VoI.5094, pp.404-411, 2003   DOI
6 Keith, Video Demystified 4th Edition, Newnes, 2004
7 A. Ollero et al, 'Techniques for reducing false alarms in infrared forest-fire automatic detection systems,' Control Engineering Practice 7, pp.123-131, 1999   DOI   ScienceOn
8 S. Briz et al, 'Reduction of false alarm rate in automatic forest fire infrared surveillance systems,' Remote Sensing of Environment 86, pp.19-29, 2003   DOI   ScienceOn
9 A. M. Tekalp, Digital Video Processing, Prentice Hall PTR, 1995
10 N. Fujiwara and K. Terada, 'Extraction of a Smoke Region Using Fractal Coding,' International Symposium on Communications and Information Technologies, pp.659-662, Sapporo, Japan, Oct. 26-29, 2004   DOI
11 B. C. Arrue et al, An Intelligent System for False Alarm Reduction in Infrared Forest-Fire Detection,' IEEE Intelligent Systems, pp.64-75, 2000   DOI   ScienceOn