摘要
为在驾驶员佩戴眼镜的情况下也能准确有效地检测疲劳状态,提出一种判断是否佩戴眼镜的方法,并建立了基于眼睛与嘴部状态的疲劳驾驶检测系统。对该系统中有关目标检测、特征提取与图像识别等算法进行研究。首先,采用Adaboost算法通过人脸分类器从视频帧中检测人脸区域,并根据面部器官几何分布规则粗检眼睛与嘴部区域;其次,基于大律法自适应二值化,采用垂直积分投影法判断是否配戴眼镜,根据灰度直方图统计特征值法判断戴眼镜的眼部区域状态,另外,利用似圆度判断嘴部打哈欠情况;最后,利用PERCLOS(Percentage of Eyelid Closure over the Pupil)值识别眼睛疲劳状态,利用打哈欠频率识别嘴部疲劳状态。当检测到驾驶员处于疲劳状态,则及时给出疲劳警告。实验结果表明,该方法可有效解决眼镜对检测的干扰,并适用于不同光照与环境。同时,在戴眼镜情况下对于眼睛与嘴部疲劳状态的判断优于其他方法。基本满足疲劳检测系统对良好的实时性、稳定性与鲁棒性等要求。
In order to recognize the fatigue state accurately under the condition of the driver wearing glasses, a method of judging whether to wear glasses is proposed. And the fatigue detection system based on the state of eyes and mouth is established. Its applied algorithms such as moving object detection, feature extraction and image recognition and etc are investigated. First, face classifier based on Adaboost algorithm is used to detect face region from the video frames. The area of eyes and mouth can be detect roughly according to the facial geometric distribution rules; Secondly, threshold adaptively by Otsu＇s method and determine whether driver wear glasses based on horizontal integral projection method. Then, identify the state of eyes with galsses according to the method of histogram part statistics characteristic values. In addition, using roundness to judge whether mouth yawn. Finally, the equivalent PERCLOS （ Percentage of Eyelid Closure over the Pupil） value is taken to identify the fatigue state of eyes, and the frequency of yawning is used to identify the fatigue state of mouth. The system give an early warning in time when it detects fatigue driving. The experimental results show that these method can solve the interference of glasses The accuracy is 95.8%. It＇s better requirements of real time, accuracy effectively, and is appropriate than the method which only use and robustness. for different illumination and surroundings. eye or mouth. It can also satisfy the system
作者
邹昕彤
王世刚
赵文婷
赵晓琳
李天舒
ZOU Xintong WANG Shigang ZHAO Wenting ZHAO Xiaolin LI Tianshu(College of Communication Engineering, Jilin University, Changchun 130012, China)
出处
《吉林大学学报（信息科学版）》
CAS
2017年第2期204-211,共8页
Journal of Jilin University（Information Science Edition）
基金
吉林省科技发展计划基金资助项目(20150204006GX)
关键词
疲劳检测
眼镜判断
直方图特征
状态识别
fatigue detection
glasses judgment
histogram feature
state recognition
