基于动静态特征的监控视频火灾检测算法

计算机科学 ›› 2019, Vol. 46 ›› Issue (6A): 284-286.

基于动静态特征的监控视频火灾检测算法

肖潇, 孔凡芝, 刘金华

浙江传媒学院电子信息学院杭州310018

出版日期:2019-06-14 发布日期:2019-07-02
作者简介:肖潇(1980－),女,博士,讲师,主要研究方向为图像处理与模式识别;孔凡芝(1973－),女,博士,讲师,主要研究方向为图像处理与模式识别;刘金华(1972－),女,硕士,高级实验师,主要研究方向为自动化技术。
基金资助:
本文受浙江省公益项目(LGG19E050002,LGG18F010001)资助。

Monitoring Video Fire Detection Algorithm Based on DynamicCharacteristics and Static Characteristics

XIAO Xiao, KONG Fan-zhi, LIU Jin-hua

College of Electronic Information,Zhejiang University of Media and Communications,Hangzhou 310018,China

Online:2019-06-14 Published:2019-07-02

摘要/Abstract

摘要： 火灾是危害公共安全和社会发展的主要灾害之一,及时、准确的火灾报警具有重大意义。基于视频的火灾检测克服了传统技术的缺点,适应环境的能力较强。结合智能检测算法,其可以提供更直观、更丰富的火灾信息。所提算法分析了视频图像中的静态特征,得到疑似火焰图像,再通过动态特征进一步判断其是否为火焰。MATLAB仿真实验证明了该算法的有效性,并且其具有较好的实用性。

关键词: 动态特征, 火灾检测, 静态特征, 漏报率, 误报率

Abstract: Fire is one of the most common hazards to public safety and social development,and timely and accurate fire alarm is of great significance.Video based fire detection overcomes the shortcomings of traditional technology and adapts to the various environment well.Combined with intelligent detection algorithm,it can provide more intuitive and richer fire information.The static characteristics of the video images are analyzed,and the suspected flame images are obtained,and then the flame is further judged by the dynamic characteristics.The effectiveness of the algorithm is proved by MATLAB in this paper and it has a good application prospect.

Key words: Dynamic characteristics, False alarm rate, Fire detection, Missing report rate, Static characteristics

中图分类号:

TP391

肖潇, 孔凡芝, 刘金华. 基于动静态特征的监控视频火灾检测算法[J]. 计算机科学, 2019, 46(6A): 284-286. https://doi.org/

XIAO Xiao, KONG Fan-zhi, LIU Jin-hua. Monitoring Video Fire Detection Algorithm Based on DynamicCharacteristics and Static Characteristics[J]. Computer Science, 2019, 46(6A): 284-286. https://doi.org/

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