Fire detection in infrared video using wavelet analysis

Behcet Uǧur Töreyin; Ramazan Gökberk Cinbiş; Yiǧithan Dedeoǧlu; Ahmet Enis Çetin

doi:10.1117/1.2748752

Fire detection in infrared video using wavelet analysis

Behcet Uǧur Töreyin^*, Ramazan Gökberk Cinbiş, Yiǧithan Dedeoǧlu, Ahmet Enis Çetin

^*Bu çalışma için yazışmadan sorumlu yazar

Bilkent University

Araştırma sonucu: Dergiye katkı › Makale › bilirkişi

63 Atıf (Scopus)

Özet

A novel method to detect flames in infrared (IR) video is proposed. Image regions containing flames appear as bright regions in IR video. In addition to ordinary motion and brightness clues, the flame flicker process is also detected by using a hidden Markov model (HMM) describing the temporal behavior. IR image frames are also analyzed spatially. Boundaries of flames are represented in wavelet domain and the high frequency nature of the boundaries of fire regions is also used as a clue to model the flame flicker. All of the temporal and spatial clues extracted from the IR video are combined to reach a final decision. False alarms due to ordinary bright moving objects are greatly reduced because of the HMM-based flicker modeling and wavelet domain boundary modeling.

Orijinal dil	İngilizce
Makale numarası	067204
Dergi	Optical Engineering
Hacim	46
Basın numarası	6
DOI'lar	https://doi.org/10.1117/1.2748752
Yayın durumu	Yayınlandı - Haz 2007
Harici olarak yayınlandı	Evet

Finansman

This work is supported in part by the Scientific and Technical Research Council of Turkey (TÜBİTAK) and European Commission 6th Framework Program with grant number FP6-507752 (MUSCLE Network of Excellence Project). We are grateful to Aselsan Inc. Microelectronics, Guidance and Electro-Optics Division (MGEO), Ankara, Turkey, for lending “ASIR Thermal Imaging System” and helping us in recording infrared fire videos.

Finansörler	Finansör numarası
European Commission 6th Framework Program	FP6-507752
TÜBİTAK
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu

Belgeye Erişim

10.1117/1.2748752

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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title = "Fire detection in infrared video using wavelet analysis",

abstract = "A novel method to detect flames in infrared (IR) video is proposed. Image regions containing flames appear as bright regions in IR video. In addition to ordinary motion and brightness clues, the flame flicker process is also detected by using a hidden Markov model (HMM) describing the temporal behavior. IR image frames are also analyzed spatially. Boundaries of flames are represented in wavelet domain and the high frequency nature of the boundaries of fire regions is also used as a clue to model the flame flicker. All of the temporal and spatial clues extracted from the IR video are combined to reach a final decision. False alarms due to ordinary bright moving objects are greatly reduced because of the HMM-based flicker modeling and wavelet domain boundary modeling.",

keywords = "Hidden Markov models, Infrared video fire detection, Segmentation, Video event detection, Video object contour analysis, Wavelet transform",

author = "T{\"o}reyin, {Behcet Uǧur} and Cinbi{\c s}, {Ramazan G{\"o}kberk} and Yiǧithan Dedeoǧlu and {\c C}etin, {Ahmet Enis}",

year = "2007",

month = jun,

doi = "10.1117/1.2748752",

language = "English",

volume = "46",

journal = "Optical Engineering",

issn = "0091-3286",

publisher = "SPIE",

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TY - JOUR

T1 - Fire detection in infrared video using wavelet analysis

AU - Töreyin, Behcet Uǧur

AU - Cinbiş, Ramazan Gökberk

AU - Dedeoǧlu, Yiǧithan

AU - Çetin, Ahmet Enis

PY - 2007/6

Y1 - 2007/6

N2 - A novel method to detect flames in infrared (IR) video is proposed. Image regions containing flames appear as bright regions in IR video. In addition to ordinary motion and brightness clues, the flame flicker process is also detected by using a hidden Markov model (HMM) describing the temporal behavior. IR image frames are also analyzed spatially. Boundaries of flames are represented in wavelet domain and the high frequency nature of the boundaries of fire regions is also used as a clue to model the flame flicker. All of the temporal and spatial clues extracted from the IR video are combined to reach a final decision. False alarms due to ordinary bright moving objects are greatly reduced because of the HMM-based flicker modeling and wavelet domain boundary modeling.

AB - A novel method to detect flames in infrared (IR) video is proposed. Image regions containing flames appear as bright regions in IR video. In addition to ordinary motion and brightness clues, the flame flicker process is also detected by using a hidden Markov model (HMM) describing the temporal behavior. IR image frames are also analyzed spatially. Boundaries of flames are represented in wavelet domain and the high frequency nature of the boundaries of fire regions is also used as a clue to model the flame flicker. All of the temporal and spatial clues extracted from the IR video are combined to reach a final decision. False alarms due to ordinary bright moving objects are greatly reduced because of the HMM-based flicker modeling and wavelet domain boundary modeling.

KW - Hidden Markov models

KW - Infrared video fire detection

KW - Segmentation

KW - Video event detection

KW - Video object contour analysis

KW - Wavelet transform

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U2 - 10.1117/1.2748752

DO - 10.1117/1.2748752

M3 - Article

AN - SCOPUS:34548017199

SN - 0091-3286

VL - 46

JO - Optical Engineering

JF - Optical Engineering

IS - 6

M1 - 067204

ER -

Fire detection in infrared video using wavelet analysis

Özet

Finansman

Belgeye Erişim

Diğer Dosyalar ve Linkler

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