一种基于人眼状态的疲劳驾驶检测系统研究

Study of Fatigue Driving Detection System based on Human Eye

笔者提出了一种基于人眼状态的疲劳驾驶检测方法,对常用疲劳监测方法进行分析对比,并和人眼状态监测方法进行比较,进一步提高人眼状态监测方法的实用性和及时性;完善基于人眼状态的疲劳驾驶检测算法,提取视频图像的边缘特征并进行二值化处理,利用Hough变换来检验瞳孔轮廓,最后达到降低噪声和边缘间断影响的目的;实现基于人眼状态的疲劳驾驶检测系统,使其更适合车辆运行时多变的光照情况及高频低幅振动的环境,进一步达到实时检测和识别的要求。

The author presents a fatigue driving detection method based on the state of the human eye.The fatigue monitoring methods are compared and compared with the human eye condition monitoring method to further improve the practicality and timeliness of the human eye condition monitoring method.The fatigue detection algorithm based on human eyes is improved,the edge features of video images are extracted and binarized,and the pupil contour is tested by Hough transform.Finally,the effect of reducing the noise and edge discontinuity is achieved.The fatigue driving detection system based on human eye state is realized,which makes it more suitable for the changeable lighting condition and high frequency low amplitude vibration environment in the vehicle running,and further meets the requirements of real-time detection and recognition.