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dc.contributor.authorTöreyin, B. Uğuren_US
dc.contributor.authorDedeoǧlu, Yiğithanen_US
dc.contributor.authorÇetin, A. Enisen_US
dc.coverage.spatialAntalya, Turkey
dc.date.accessioned2016-02-08T11:50:03Z
dc.date.available2016-02-08T11:50:03Z
dc.date.issued2005-09en_US
dc.identifier.urihttp://hdl.handle.net/11693/27298
dc.descriptionDate of Conference: 4-8 Sept. 2005
dc.descriptionConference name: 13th European Signal Processing Conference, 2005
dc.description.abstractA method for smoke detection in video is proposed. It is assumed the camera monitoring the scene is stationary. Since the smoke is semi-transparent, edges of image frames start loosing their sharpness and this leads to a decrease in the high frequency content of the image. To determine the smoke in the field of view of the camera, the background of the scene is estimated and decrease of high frequency energy of the scene is monitored using the spatial wavelet transforms of the current and the background images. Edges of the scene are especially important because they produce local extrema in the wavelet domain. A decrease in values of local extrema is also an indicator of smoke. In addition, scene becomes grayish when there is smoke and this leads to a decrease in chrominance values of pixels. Periodic behavior in smoke boundaries and convexity of smoke regions are also analyzed. All of these clues are combined to reach a final decision.en_US
dc.language.isoEnglishen_US
dc.source.title13th European Signal Processing Conference, EUSIPCO 2005en_US
dc.relation.isversionofhttps://ieeexplore.ieee.org/document/7077943
dc.subjectBackground imageen_US
dc.subjectField of viewsen_US
dc.subjectFinal decisionen_US
dc.subjectHigh frequencyen_US
dc.subjectImage framesen_US
dc.subjectLocal extremumen_US
dc.subjectPeriodic behavioren_US
dc.subjectSemi-transparenten_US
dc.subjectSmoke detectionen_US
dc.subjectWavelet domainen_US
dc.subjectCamerasen_US
dc.subjectSmoke detectorsen_US
dc.subjectWavelet analysisen_US
dc.subjectSmokeen_US
dc.titleWavelet based real-time smoke detection in videoen_US
dc.typeConference Paperen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage293en_US
dc.citation.epage296en_US
dc.publisherIEEE
dc.contributor.bilkentauthorÇetin, A. Enis


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