Vision based forest smoke detection using analyzing of temporal patterns of smoke and their probability models

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 7877, Issue , 2011, Pages

  Ham, SunJae ^a   Ko, Byoung Chul ^a   Nam, Jae Yeal ^a  

^a Keimyung University   (South Korea)

Author keywords

event; forest smoke detection; fuzzy finite automata; probability density function; state

Indexed keywords

DETECTION PERFORMANCE; EARLY FIRE; EVENT; FOREST-SMOKE DETECTION; FUZZY FINITE AUTOMATA; FUZZY STATE; INTENSITY ENTROPIES; MAIN CHARACTERISTICS; MULTI-VARIATE PROBABILITY DENSITY FUNCTIONS; PROBABILITY MODELS; SMOKE DETECTION; STATE; TEMPORAL PATTERN; TIME-DEPENDENT; VISION BASED; WAVELET ENERGY;

ALGORITHMS; COMPUTER VISION; FIRE DETECTORS; FIRES; IMAGING SYSTEMS; PROBABILITY; SMOKE; SMOKE DETECTORS; VIDEO CAMERAS;

PROBABILITY DENSITY FUNCTION;

EID: 79953152679     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.871995     Document Type: Conference Paper

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