tailieunhanh - Smoke detection in video based on motion and contrast

An efficient smoke detection algorithm on color video sequences obtained from a stationary camera is proposed. Our algorithm considers dynamic and static features of smoke and composed of basic steps: preprocessing; slowly moving areas and pixels segmentation in a current input frame based on adaptive background subtraction; merge slowly moving areas with pixels into blobs; classification of the blobs obtained before. | Journal of Computer Science and Cybernetics, , (2012), 195 205 SMOKE DETECTION IN VIDEO BASED ON MOTION AND CONTRAST N. BROVKO1 , R. BOGUSH1 , S. ABLAMEYKO2 1 Polotsk State University, 29, Blokhin str., Novopolotsk, Belarus 2 Belarusian State University, 4, Nezavisimosti av., Minsk, Belarus Tóm t t. B i b¡o · xu§t mët thuªt to¡n húu hi»u ph¡t hi»n khâi trong video m u tø m¡y quay camera t¾nh. Thuªt to¡n xem x²t c¡c °c tr÷ng ëng v t¾nh cõa khâi bao gçm c¡c b÷îc cì b£n: Ti·n sû l½; C¡c mi·n di chuyºn chªm v c¡c ph¥n o¤n £nh iºm trong khung dú li»u nhªp düa tr¶n kh§u trø th½ch nghi; Hñp nh§t c¡c mi·n dàch chuyºn chªm vîi c¡c iºm £nh th nh c¡c giåt n÷îc; Ph¥n lo¤i c¡c giåt n÷îc. B i b¡o ¢ sû döng ph÷ìng ph¡p kh§u trø th½ch nghi tr¶n tøng giai o¤n ph¡t triºn khâi. Ph¥n lo¤i c¡c giåt n÷îc di ëng düa tr¶n t½nh to¡n c¡c dáng quang håc, tr¶n sü ph¥n t½ch t÷ìng ph£n Weber v câ t½nh ¸n h÷îng khâi lan täa. Phèi hñp gi¡m s¡t c¡c h¼nh £nh video thªt ÷ñc sû döng º ph¡t hi»n khâi. C¡c k¸t qu£ thüc nghi»m công ÷ñc ÷a ra. Abstract. An efficient smoke detection algorithm on color video sequences obtained from a stationary camera is proposed. Our algorithm considers dynamic and static features of smoke and composed of basic steps: preprocessing; slowly moving areas and pixels segmentation in a current input frame based on adaptive background subtraction; merge slowly moving areas with pixels into blobs; classification of the blobs obtained before. We use adaptive background subtraction at a stage of moving detection. Moving blobs classification is based on optical flow calculation, Weber contrast analysis and takes into account primary direction of smoke propagation. Real video surveillance sequences are used for smoke detection with utilization our algorithm. A set of experimental results are presented in the paper. Keywords. smoke detection, video sequences, background subtraction, Weber contrast analysis 1. INTRODUCTION Reliable and early fire detection