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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | SunJae Ham ByoungChul Ko JaeYeal Nam |
| Copyright Year | 2010 |
| Abstract | This paper proposes a new fire-flame detection method using probabilistic membership function of visual features and Fuzzy Finite Automata (FFA). First, moving regions are detected by analyzing the background subtraction and candidate flame regions then identified by applying flame color models. Since flame regions generally have an irregular pattern continuously, membership functions of variance of intensity, wavelet energy and motion orientation are generate and applied to FFA. Since FFA combines the capabilities of automata with fuzzy logic, it not only provides a systemic approach to handle uncertainty in computational systems, but also can handle continuous spaces. The proposed algorithm is successfully applied to various fire videos and shows a better detection performance when compared with other methods |
| Starting Page | 3919 |
| Ending Page | 3922 |
| File Size | 703988 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424475421 |
| ISSN | 10514651 |
| e-ISBN | 9781424475414 |
| DOI | 10.1109/ICPR.2010.953 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-08-23 |
| Publisher Place | Turkey |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Fires Automata Videos Mathematical model Motion pictures Feature extraction Fuzzy logic fuzzy logic Fire-flame FFA probabilistic membership function background subtraction |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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