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Vision-based fire detection algorithm using optical flow

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dc.contributor.authorHa, Changwoo-
dc.contributor.authorHwang, Ung-
dc.contributor.authorJeon, Gwanggil-
dc.contributor.authorCho, Joongwhee-
dc.contributor.authorJeong, Jechang-
dc.date.accessioned2022-07-16T14:44:09Z-
dc.date.available2022-07-16T14:44:09Z-
dc.date.created2021-05-11-
dc.date.issued2012-07-
dc.identifier.issn0000-0000-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/165216-
dc.description.abstractRecently automatic video surveillance in the digital video recording CCTV system is rapidly becoming one of the most accepted security system. The dangerous situations such as forest fire, flood, and terrorism are increasing, and cause serious casualty and property loss. In this paper, we particularly focus on the fire detection system in video. The proposed block-based fire detection algorithm consists of three basic steps. In the first step, we find motion vector utilizing optical flow and distinguish the suspect as fire region. In the second step, we conduct chromatic detection based on Lab color space. In the final step, we employ motion information for detecting the correct fire block by using the characteristics that fire goes almost upward. Experimental results show that the proposed method yields good performance for fire detection.-
dc.language영어-
dc.language.isoen-
dc.publisherIEEE-
dc.titleVision-based fire detection algorithm using optical flow-
dc.typeArticle-
dc.contributor.affiliatedAuthorJeong, Jechang-
dc.identifier.doi10.1109/CISIS.2012.25-
dc.identifier.scopusid2-s2.0-84866603509-
dc.identifier.bibliographicCitationProceedings - 2012 6th International Conference on Complex, Intelligent, and Software Intensive Systems, CISIS 2012, pp.526 - 530-
dc.relation.isPartOfProceedings - 2012 6th International Conference on Complex, Intelligent, and Software Intensive Systems, CISIS 2012-
dc.citation.titleProceedings - 2012 6th International Conference on Complex, Intelligent, and Software Intensive Systems, CISIS 2012-
dc.citation.startPage526-
dc.citation.endPage530-
dc.type.rimsART-
dc.type.docTypeConference Paper-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordPlusDangerous situations-
dc.subject.keywordPlusDigital video recording-
dc.subject.keywordPlusFire detection-
dc.subject.keywordPlusFire detection systems-
dc.subject.keywordPlusForest fires-
dc.subject.keywordPlusLab color space-
dc.subject.keywordPlusMotion information-
dc.subject.keywordPlusMotion Vectors-
dc.subject.keywordPlusProperty loss-
dc.subject.keywordPlusVideo surveillance-
dc.subject.keywordPlusVision based-
dc.subject.keywordPlusDeforestation-
dc.subject.keywordPlusOptical flows-
dc.subject.keywordPlusSecurity systems-
dc.subject.keywordPlusSignal detection-
dc.subject.keywordPlusFire detectors-
dc.subject.keywordPlusAlgorithms-
dc.subject.keywordPlusData Storage-
dc.subject.keywordPlusDeforestation-
dc.subject.keywordPlusFire Detectors-
dc.subject.keywordPlusFloods-
dc.subject.keywordPlusForest Fires-
dc.subject.keywordPlusSignals-
dc.identifier.urlhttps://ieeexplore.ieee.org/document/6245623-
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