标题:A flame detection algorithm based on Bag-of-Features in the YUV color space
作者:Liu, Zhao-Guang ;Zhang, Xing-Yu ;Yang-Yang ;Wu, Ceng-Ceng
作者机构:[Liu, Zhao-Guang ;Zhang, Xing-Yu ;Yang-Yang ] School of Information Science and Engineering, Shandong University, Jinan, China;[Wu, Ceng-Ceng ] School 更多
会议名称:2015 International Conference on Intelligent Computing and Internet of Things, ICIT 2015
会议日期:17 January 2015 through 18 January 2015
来源:Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things, ICIT 2015
出版年:2015
页码:64-67
DOI:10.1109/ICAIOT.2015.7111539
关键词:Bag-of-Features; flame detection; YUV color space
摘要:Computer vision-based fire detection involves flame detection and smoke detection. This paper proposes a new flame detection algorithm, which is based on a Bag-of-Features technique in the YUV color space. Inspired by that the color of flame in image and video will fall in certain regions in the color space, models of flame pixels and non-flame pixels are established based on code book in the training phase in our proposal. In the testing phase, the input image is split into some N×N blocks and each block is classified respectively. In each N×N block, the pixels values in the YUV color space are extracted as features, just as in the training phase. According to the experimental results, our proposed method can reduce the number of false alarms greatly compared with an alternative algorithm, while it also ensures the accurate classification of positive samples. The classification performance of our proposed method is better than that of alternative algorithms. © 2015 IEEE.
收录类别:EI;SCOPUS
Scopus被引频次:6
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938076749&doi=10.1109%2fICAIOT.2015.7111539&partnerID=40&md5=8423c32afdcbc443aaeffc4ebfbccc34
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