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.
| Original language | English |
|---|---|
| Article number | 067204 |
| Journal | Optical Engineering |
| Volume | 46 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Jun 2007 |
| Externally published | Yes |
Funding
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.
| Funders | Funder number |
|---|---|
| European Commission 6th Framework Program | FP6-507752 |
| TÜBİTAK | |
| Türkiye Bilimsel ve Teknolojik Araştirma Kurumu |
Keywords
- Hidden Markov models
- Infrared video fire detection
- Segmentation
- Video event detection
- Video object contour analysis
- Wavelet transform