SMOKE DETECTION ALGORITHM FOR VIDEO SURVEILLANCE SYSTEMS
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Abstract
This paper presented an efficient and reliable smoke detection algorithm on the video sequences. The key components developed in this algorithm are slowly moving blobs detection, classification of the blobs obtained and smoke regions tracking. We use preprocessing, slowly moving areas and pixels segmentation in a current input frame based on adaptive background subtraction algorithm, merge of the slowly moving areas and pixels into blobs at a stage slowly moving blobs detection. Calculation of Weber contrast is applied to classification and the primary direction of smoke propagation is considered. On a tracking step we trace texture and color smoke features using Cam Shift algorithm. The performed experiments have shown that our smoke detector quickly and reliable finds out a smoke on a complex dynamic scene. Experimental results are presented.
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References
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