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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Byoung Chul Ko Sun Jae Ham Jae Yeal Nam |
| Copyright Year | 1991 |
| Abstract | Fire-flame detection using a video camera is difficult because a flame has irregular characteristics, i.e., vague shapes and color patterns. Therefore, in this paper, we propose a novel fire-flame detection method using fuzzy finite automata (FFA) with probability density functions based on visual features, thereby providing a systemic approach to handling irregularity in computational systems and the ability to handle continuous spaces by combining the capabilities of automata with fuzzy logic. First, moving regions are detected via background subtraction, and the candidate flame regions are then identified by applying flame color models. In general, flame regions have a continuous irregular pattern; therefore, probability density functions are generated for the variation in intensity, wavelet energy, and motion orientation and applied to the FFA. The proposed algorithm is successfully applied to various fire/non-fire videos, and its detection performance is better than that of other methods. |
| Sponsorship | IEEE Circuits and Systems Society |
| Starting Page | 1903 |
| Ending Page | 1912 |
| Page Count | 10 |
| File Size | 948229 |
| File Format | |
| ISSN | 10518215 |
| Volume Number | 21 |
| Issue Number | 12 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-12-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Fires Automata Mathematical model Image color analysis Computational modeling Probability density function state transition FFA flame verification probability density function skewness |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering Media Technology |
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