Fire surveillance method based on quaternionic wavelet features

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5916 LNCS, Issue , 2009, Pages 477-488

  Yu, Zhou ^a,b   Xu, Yi ^a,b   Yang, Xiaokang ^a,b  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b Shanghai Key Laboratory of Materials Laser Processing and Modification   (China)

Author keywords

Fire Surveillance; Flame recognition; Quaternionic features; Smoke detection

Indexed keywords

COLOR CHANNELS; COLOR PIXELS; COLOR SPACE; COMPREHENSIVE ANALYSIS; DYNAMIC TEXTURES; FALSE ALARMS; FIRE EVENT; FIRE RECOGNITION; FIRE SURVEILLANCE; FIRE SURVEILLANCE SYSTEM; GABOR WAVELETS; GAUSSIAN KERNELS; HIGH DETECTION RATE; MOVING OBJECTS; QUANTITATIVE MEASURES; SMOKE DETECTION; SPECTRAL DISTRIBUTION; SURVEILLANCE METHODS; TEMPORAL CHARACTERISTICS; TEMPORAL FILTERS; VISION BASED; WAVELET FEATURES;

BANDPASS FILTERS; COLOR; FIRE DETECTORS; FLAMMABILITY; MONITORING; PIXELS; SMOKE; SMOKE DETECTORS;

FIRES;

EID: 77249139718     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-11301-7_48     Document Type: Conference Paper

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