基于色素分布的驾驶员面部特征点的定位方法

利用嘴唇和眼睛色素分布定位驾驶员面部特征点,首先根据嘴唇为红色这一特征,对CCD采集的彩色图像进行亮度规一化处理后,再向由色彩信息构成的UV空间坐标系投影,根据红色素从投影中分割出嘴唇区域,用边缘提取和红色像素点相结合的方法确定嘴唇形状;采用夹逼法确定描述嘴部状态的特征点.根据人脸结构尺寸,初步确定眼睛区域,根据眼睛为黑色的特征,采用与嘴巴相同的方法,确定识别眼睛张开和闭合状态的特征点.实验结果表明,该方法可以有效去除嘴唇和眼睛周围的阴影干扰,无论光线是否均匀,该算法的准确率均达到94.3%以上,该算法具有实时、准确的特点,为进一步判断驾驶员是否处于疲劳状态提供重要的判断依据.

Method to Locate Driver's Face Feature Points by Chrominance Distribution

A new method is proposed to locate a driver's face feature points by chrominance distribution.Based on the face that human lips are red,the luminance of color images acquired by CCD is normalized and the images are projected into an UV space coordinate system composed of color data.Separating the lip region from the projection of images in accordance to red chrominance,the shape of lips is determined by way of combining edge extraction with red pixels,with the state feature points of mouth determined by way of bracketing and approaching.Then,the eye region is preliminarily determined according to face figure/size and,based on the fact that Chinese eyeballs are mostly black,the same method is used to determine and identify the state feature points during eye closing/opening.Experimental results showed that the method proposed is effective to getting rid of the shadow disturbance around lips and eyes,regardless of whether the luminance is even,with an accuracy offered up to higher than 94.3%.The method is thus regarded as real time,accurate and available to be an important criterion for whether a driver is in a state of tiredness.