Title :
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
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;
Conference_Titel :
Computational Intelligence and Cybernetics (CYBERNETICSCOM), 2013 IEEE International Conference on
Conference_Location :
Yogyakarta
DOI :
10.1109/CyberneticsCom.2013.6865801
