Visual-based fire detection using local binary pattern-three orthogonal planes

Author

Sthevanie, Febryanti ; Nugroho, Heru ; Yulianto, Fazmah Arif

Author_Institution

Telkom Eng. Sch., Telkom Univ., Bandung, Indonesia

fYear

2013

fDate

3-4 Dec. 2013

Firstpage

155

Lastpage

159

Abstract

This paper discussed a proposed method to detect fire with the main focus is to extract the fire features to increase the accuracy and using LBP-TOP feature extraction scheme to accelerate the process. The fire features produced by LBP-TOP was modeled by using dustering K-Means method as the reference model when the classification process was done by using K-NN method. By using those methods, the accuracy of the detection process can reach 92% and the computational cost can be reduced.

Keywords

feature extraction; fires; image classification; image colour analysis; image motion analysis; object detection; pattern clustering; K-NN method; LBP-TOP feature extraction scheme; classification process; color detection part; computational cost reduction; dynamic color detection part; fire feature extraction; k-means clustering method; local binary pattern-three orthogonal planes; motion detection frequency part; motion detection part; reference model; visual-based fire detection; Accuracy; Feature extraction; Fires; Histograms; Image color analysis; Testing; Yttrium; LBP-TOP; feature extraction; fire detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Cybernetics (CYBERNETICSCOM), 2013 IEEE International Conference on

Conference_Location

Yogyakarta

Type

conf

DOI

10.1109/CyberneticsCom.2013.6865801

Filename

6865801