驾驶员疲劳检测中眼睛特征提取算法研究  

Research on Extraction Algorithm of Eye Characteristic Parameters in Driver's Fatigue Detection

作　　者：杨非[1] 庞玉[2] 刘宗强[3] 

机构地区：[1]山东凯文科技职业学院机械工程学院,济南250200 [2]济宁市技师学院,济宁272000 [3]山推工程机械股份有限公司,济宁272073

出　　处：《机电一体化》2017年第7期23-28,63,共7页Mechatronics

摘　　要：针对当前驾驶员疲劳检测过程中眼睛特征提取方法鲁棒性较差,且定位不准的问题,提出了一种驾驶员疲劳检测中眼睛特征提取方法。首先通过基于图像增强的ASM算法对人脸特征进行定位,利用模型中的定位点提取眼睛区域,在眼睛初步定位的基础上,分别利用加权混合投影算法和多特征融合的方法对内外眼角进行精确定位;然后根据内外眼角确定瞳孔区域,采用基于灰度分布的加权积分投影算法对瞳孔中心进行粗定位,利用形态学原理对瞳孔中心进行校正,从而得到瞳孔的精确位置;最后根据准确定位提取眼睛中点的上下眼睑点,从而获取眼睛开度的大小。试验表明,该算法能准确定位瞳孔和眼角位置,并利用定位点正确提取眼睛特征。In this paper,a method of eye feature extraction in driver fatigue detection is proposed to solve the problem that the feature extraction method is poor and the location is not accurate.Firstly,ASM algorithm based on image enhancement of facial feature localization,eye region extraction using location model,based on the preliminary set eyes,respectively by using the weighted hybrid projection algorithm and multi feature fusion method to locate the corners; then according to the determined pupil area inside and outside corners,using the weighted integral projection the algorithm of gray distribution based on pupil center of the coarse positioning of the pupil center were corrected by using morphological principle,so as to obtain the precise position of the pupil; finally,according to the accurate positioning of two eye corner extraction point on the lower eyelid eyes point to get eye opening size.In this paper,experiments are carried out to test the above methods.The results show that the algorithm can accurately locate the pupil and eye corner,and use the location point to extract the eye features.

关 键 词：眼睛特征提取 瞳孔定位 眼角定位 加权积分投影 加权混合投影 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]