完整後設資料紀錄
DC 欄位語言
dc.contributor.authorChou, Kuang-Penen_US
dc.contributor.authorPrasad, Mukeshen_US
dc.contributor.authorGupta, Deepaken_US
dc.contributor.authorSankar, Sharmien_US
dc.contributor.authorXu, Ting-Weien_US
dc.contributor.authorSundaram, Sureshen_US
dc.contributor.authorLin, Chin-Tengen_US
dc.contributor.authorLin, Wen-Chiehen_US
dc.date.accessioned2018-08-21T05:57:14Z-
dc.date.available2018-08-21T05:57:14Z-
dc.date.issued2017-01-01en_US
dc.identifier.urihttp://hdl.handle.net/11536/147212-
dc.description.abstractEvery year the fire disaster always causes a lot of casualties and property damage. Many researchers are involved in the study of related disaster prevention. Early warning systems and stable fire can significantly reduce the damage caused by fire. Many existing image-based early warning systems can perform well in a particular field. In this paper, we propose a general framework that can be applied in most realistic environments. The proposed system is based on a block-based feature extraction method, which analyses local information in separate regions leading to a reduction in computing data. Local features of fire block are extracted from the detailed characteristics of fire objects, which include fire color, fire source immobility, and disorder. Each local feature has high detection rate and filter out different false-positive cases. Global analysis with fire texture and non-moving properties are applied to further reduce false alarm rate. The proposed system is composed of algorithms with low computation. Through a series of experiments, it can be observed that Experimental results show that the proposed system has higher detection rate and low false alarm rate under various environment.en_US
dc.language.isoen_USen_US
dc.subjectvideo surveillanceen_US
dc.subjectfeature extractionen_US
dc.subjectdisorder analysisen_US
dc.titleBlock-based Feature Extraction Model for Early Fire Detectionen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI)en_US
dc.citation.spage3540en_US
dc.citation.epage3547en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000428251403085en_US
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