Covariance matrix-based fire and flame detection method in video

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buir.contributor.authorÇetin, A. Enis
buir.contributor.orcidÇetin, A. Enis|0000-0002-3449-1958
dc.citation.epage1113en_US
dc.citation.issueNumber6en_US
dc.citation.spage1103en_US
dc.citation.volumeNumber23en_US
dc.contributor.authorHabiboğlu, Y. H.en_US
dc.contributor.authorGünay, O.en_US
dc.contributor.authorÇetin, A. Enisen_US
dc.date.accessioned2016-02-08T09:44:06Z
dc.date.available2016-02-08T09:44:06Z
dc.date.issued2011-09-17en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractThis paper proposes a video-based fire detection system which uses color, spatial and temporal information. The system divides the video into spatio-temporal blocks and uses covariance-based features extracted from these blocks to detect fire. Feature vectors take advantage of both the spatial and the temporal characteristics of flame-colored regions. The extracted features are trained and tested using a support vector machine (SVM) classifier. The system does not use a background subtraction method to segment moving regions and can be used, to some extent, with non-stationary cameras. The computationally efficient method can process 320×240 video frames at around 20 frames per second in an ordinary PC with a dual core 2.2 GHz processor. In addition, it is shown to outperform a previous method in terms of detection performance.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T09:44:06Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2012en
dc.identifier.doi10.1007/s00138-011-0369-1en_US
dc.identifier.issn0932-8092
dc.identifier.urihttp://hdl.handle.net/11693/21275
dc.language.isoEnglishen_US
dc.publisherSpringeren_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s00138-011-0369-1en_US
dc.source.titleMachine Vision and Applicationsen_US
dc.subjectCovariance descriptorsen_US
dc.subjectFire detectionen_US
dc.subjectSupport vector machinesen_US
dc.subjectBackground subtraction methoden_US
dc.subjectComputationally efficienten_US
dc.subjectDescriptorsen_US
dc.subjectDetection performanceen_US
dc.subjectDual coreen_US
dc.subjectFeature vectorsen_US
dc.subjectFire detectionen_US
dc.subjectFire detection systemsen_US
dc.subjectFlame detectionen_US
dc.subjectFrames per secondsen_US
dc.subjectMoving regionsen_US
dc.subjectNonstationaryen_US
dc.subjectSpatio-temporalen_US
dc.subjectTemporal characteristicsen_US
dc.subjectTemporal informationen_US
dc.subjectVideo frameen_US
dc.subjectCovariance matrixen_US
dc.subjectFire detectorsen_US
dc.subjectSupport vector machinesen_US
dc.titleCovariance matrix-based fire and flame detection method in videoen_US
dc.typeArticleen_US

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