摘要
当前火焰识别技术发展较快,多从动态与静态特征对火焰进行识别与分割,但识别误差仍然很大,同时火焰识别算法对硬件的高依赖性导致其难以适用于居民住宅。为解决这些问题,本文以树莓派3B开发板作为硬件基础设施,结合数字图像处理技术,设计出一种基于树莓派与计算机视觉的家庭火灾报警系统。首先使用传统火焰识别算法对火焰区域进行分割,并结合SVM算法对火焰进行识别与分类,准确率达到了97%,最后做出决策,判断是否向居民发出预警信息。系统可扩展性强,且成本较低,可普遍适用于居民住宅。
At present,the flame recognition technology develops rapidly,which mostly uses the dynamic and static characteristics to identify and segment the flame.But the problems are that recognition error rate is still very high,and the high dependence of the flame recognition algorithm on hardware makes it difficult to apply to residential buildings.In this paper,a home fire alarm system based on Raspberry Pi and computer vision is designed to solve these problems,which takes the Raspberry Pi 3 B development board as the hardware infrastructure and combines digital image processing technology.Firstly,traditional flame recognition algorithm was used to segment the flame area,and then SVM algorithm was used to identify and classify the flame,with an accuracy rate of 97%.Finally,a decision was made to decide whether to send warning information to residents.The system has strong expansibility and low cost,which can be widely used in residential buildings.
作者
汪乐章
林娴
唐伊文
张国平
Wang Yuezhang;Lin Xian;Tang Yiwen;Zhang Guoping(Department of Information technology,Huazhong Normal University,Wuhan 430079,China)
出处
《电子测量技术》
2019年第8期83-87,共5页
Electronic Measurement Technology
关键词
火焰识别
树莓派
计算机视觉
SVM算法
flame recognition
Raspberry Pi
computer vision
SVM algorithm
