【摘要】 采用CCD摄像机获得驾驶员脸部图像.由于黑天光线不足,肤色较暗,在将彩色图像转变为黑白图像的过程中,首先通过腐蚀和膨胀结合的方法去除图像部分的噪声.采用图像差异的阈值处理方法,初步选定灰度阈值,再利用二次非线性方程对灰度值进行归一化处理,强化了图像灰度集中各灰度值之间的差异,以此灰度阈值作为分割人脸和背景的界限值,得到图像的灰度直方图,再把灰度直方图向水平和垂直方向投影,获得驾驶员脸部区域,实现对驾驶员面部定位.该方法可以在昏暗光线下,定位人脸区域,有效去除干扰.根据上述算法,进行了不同环境和路况下的监控试验.结果表明:在昏暗光线下。驾驶员脸部定位的平均准确率达到83%,该方法具有实时、准确的特点,为进一步识别驾驶员在夜间是否处于疲劳状态提供重要的判断依据.更多还原

【Abstract】 To analyse the color image of driver’s face taken by CCD camera under obscure conditions,the image noise jamming is eliminated first by erosion in combination with dilation operation,and the threshold processing is used for the grey level differences in the image to select preliminarily the threshold value of grey level.Then,a nonlinear quadratic equation is used to normalize the grey levels so as to intensify the difference among the grey levels and get again the threshold value which is taken as the segmentation threshold between human face and background.By projecting the grey image both horizontally and vertically,the face area can be determined to implement the face locating.Monitoring tests were carried out in different environments and on different roads in accordance to the method proposed,and the results showed that the mean accuracy comes up to 83% under obscure conditions with the advantages of real time and accurate.It benefits judging if a driver is tired in evening.更多还原