基于嘴唇色度Fisher分类的驾驶疲劳视觉检测

Vision detection of driving fatigue based on lip chroma Fisher classifier

为提高驾驶疲劳检测的准确率和可靠性,利用唇色和肤色的色度分布差异,挑选3个典型颜色特征构建Fisher分类器用于提取唇色区域.采用区域连通算法对二值唇色区域进行滤波处理,运用改进积分投影算法确定嘴唇边界,根据嘴巴开合度及打呵欠频率判断驾驶员是否疲劳.实验结果表明:基于3个颜色特征构建的Fisher分类器在唇色提取效果上明显优于单一颜色特征的提取效果;改进的积分投影算法能提高嘴唇边界定位的精度和速度;基于打呵欠频率的驾驶疲劳检测方法具有更优的检测准确率和可靠性.融合多个典型颜色特征可改善唇色提取的鲁棒性和可靠性,有助于驾驶疲劳检测效果的提高.

To improve the accuracy and reliability of driving fatigue detection, three typical color characters are se- lected to construct the Fisher classifier for extracting lip region based on chroma distribution diversity. Region con- necting algorithm is used to filter the noise in binary lip area. Improved integral projection algorithm is adopted to locate the lip boundary. Whether drivers are fatigued is recognized by the open-close degree of mouth and yawning frequency. Experiments show that the Fisher classifier based on three color characters has obvious superiority over that based on single color character in lip color extraction, the improved integral projection algorithm can enhance the accuracy and speed of locating lip boundary, and the driving fatigue detection based on yawning frequency has better accuracy and reliability. Fusing multi-color characters can promote the detection result of driving fatigue on the premise of ameliorating the robustness and reliability of lip color extraction.