Fire Detection Algorithm Combined with Image Processing and Flame Emission Spectroscopy

Fire Detection Algorithm Combined with Image Processing and Flame Emission Spectroscopy Fire Technology 2018 Springer Science+Business Media, LLC, part of Springer Nature. Manufactured in The United States https://doi.org/10.1007/s10694-018-0727-x Fire Detection Algorithm Combined with Image Processing and Flame Emission Spectroscopy Xuanbing Qiu* , Tingyu Xi, Dongyuan Sun, Enhua Zhang, Chuanliang Li*, Ying Peng, and Jilin Wei, School of Applied Science, Taiyuan University of Science and Technology, Taiyuan 030024, China Gao Wang*, State Key Laboratory for Electronic Test Technology, North University of China, Taiyuan 030051, China Received: 6 January 2018/Accepted: 28 April 2018 Abstract. Fire poses a significant risk to the safety, health, and property of people around the world. However, traditional ‘‘point sensor’’ fire detection techniques for indoor buildings based on air particles, air temperatures, and smoke have a low sen- sitivity, long response time, and poor stability. Therefore, video-based fire detection has become a particularly efficient and important method for detecting the early signs of a fire. Due to image blur, low illumination, flame-like interference and other fac- tors, there is a certain error rate of fire recognition using video flame recognition methods. According to our previous study of a multi-feature flame recognition algo- rithm, a novel flame recognition algorithm based on free radical emission spec- troscopy during combustion is http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Fire Technology Springer Journals

Fire Detection Algorithm Combined with Image Processing and Flame Emission Spectroscopy

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Publisher
Springer US
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Engineering; Civil Engineering; Classical Mechanics; Characterization and Evaluation of Materials; Physics, general
ISSN
0015-2684
eISSN
1572-8099
D.O.I.
10.1007/s10694-018-0727-x
Publisher site
See Article on Publisher Site

Abstract

Fire Technology 2018 Springer Science+Business Media, LLC, part of Springer Nature. Manufactured in The United States https://doi.org/10.1007/s10694-018-0727-x Fire Detection Algorithm Combined with Image Processing and Flame Emission Spectroscopy Xuanbing Qiu* , Tingyu Xi, Dongyuan Sun, Enhua Zhang, Chuanliang Li*, Ying Peng, and Jilin Wei, School of Applied Science, Taiyuan University of Science and Technology, Taiyuan 030024, China Gao Wang*, State Key Laboratory for Electronic Test Technology, North University of China, Taiyuan 030051, China Received: 6 January 2018/Accepted: 28 April 2018 Abstract. Fire poses a significant risk to the safety, health, and property of people around the world. However, traditional ‘‘point sensor’’ fire detection techniques for indoor buildings based on air particles, air temperatures, and smoke have a low sen- sitivity, long response time, and poor stability. Therefore, video-based fire detection has become a particularly efficient and important method for detecting the early signs of a fire. Due to image blur, low illumination, flame-like interference and other fac- tors, there is a certain error rate of fire recognition using video flame recognition methods. According to our previous study of a multi-feature flame recognition algo- rithm, a novel flame recognition algorithm based on free radical emission spec- troscopy during combustion is

Journal

Fire TechnologySpringer Journals

Published: Jun 2, 2018

References

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