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Time Frame Selection Based Feature Extraction for Fire Detection in Video Surveillance

Shidik, Guruh Fajar and Adnan, Fajrian Nur (2011) Time Frame Selection Based Feature Extraction for Fire Detection in Video Surveillance. Document Repository.

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This research proposed new simple feature extraction method to characterize the feature of fire that capable to be used in classifying an object as fire or neither in video surveillance for fire detection. The process of extraction feature consists with simple segmentation process in color domain, and the movement. Time frame selection is proposed to select specific video frames that will be extracted and will be placed as key feature or attribute by calculate the number of binary histogram level. We using classification method Back-Propagation Neural Network to classify the features that has been generates and evaluates its accuracy. The result of this experiment has showed the performance of method could give accuracy until 76.67% in classifying video fire detection. ISTIE 2014 and Journal of Computational and Theoretical Nanoscience http://eprints.dinus.ac.id/14130/1/IEEE_Conference_-_Time_Frame_Selection_Based_Feature_Extraction_for_Fire_Detection_in_Video_Surveillance.pdf

Item Type: Article
Subjects: T Technology > Teknik Informatika
Universitas Dian Nuswantoro > Fakultas Ilmu Komputer > Teknik Informatika
Divisions: Library of Congress Subject Areas > T Technology > Teknik Informatika
Fakultas Ilmu Komputer > Teknik Informatika
Depositing User: Psi Udinus
Date Deposited: 28 Jan 2015 14:55
Last Modified: 13 Oct 2015 14:31
URI: http://eprints.dinus.ac.id/id/eprint/14618

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