摘要
如今汽车已成为人们出行的首选工具之一,疲劳驾驶便成了一项重大安全隐患。提出基于眼、嘴、头等多种面部特征相结合的疲劳驾驶检测方法。该方法使用CCD摄像头采集图像信息,进行图像预处理,通过基于adaboost算法的人脸检测方法,采用灰度积分投影定位眼、嘴区域,来监测局部状态。改进的D-S信息融合算法形成综合疲劳判断指标,当指标达疲劳值时基于IPv6的预警平台会及时发出预警。将多种信号特征相融合保证了系统的可靠性与高效性。
Nowadays,automobiles have became one of the preferred travel tools for people,and then fatigue driving has became a major safety hazard.Summarizing the advantages and disadvantages of previous fatigue driving research,a fatigue driving detection method based on the combination of various signal characteristics of eyes,mouth and head was proposed.CCD camera was used to collect image information and perform image preprocessing,through face detection based on adaboost algorithm,using gray integral projection to locate eye,mouth area,monitor local state,form comprehensive fatigue judgment index,when the indicator reaches a certain value.An early warning was issued.The integration of multiple signal features ensures the reliability and efficiency of the system.
作者
郭慧利
王恁
郭浩
GUO Huili;WANG Nen;GUO Hao(School of Information and Computer,Taiyuan University of Technology,Jinzhong 030600,China)
出处
《通信学报》
EI
CSCD
北大核心
2018年第A01期22-29,共8页
Journal on Communications
关键词
疲劳驾驶
图像预处理
人脸检测
灰度积分投影
信息融合算法
IPV6
fatigue driving
image preprocessing
face detection
grayscale integral projection,information fusion algorithm
IPv6
