驾驶员疲劳检测中的眼睛定位与状态分析

针对驾驶员头部多角度变化时眼睛定位困难的现状,提出了基于肤色检测和纹理特征的驾驶员眼睛定位算法.该算法采用肤色检测定位出人脸图像；根据眼睛灰度范围与其他部位的差异进行人脸图像二值化和形态学图像处理,确定眼睛候选区域；通过比较各候选区域纹理特征向量值的不同,确定眼睛位置,并基于黑斑拟合椭圆性质进行眼睛验证和睁开程度计算.计算结果表明,头部角度变化时各候选区域的纹理特征值差别仍较大.因此,该算法不受驾驶员头部角度的影响,眼睛定位准确率较高,且算法简单,计算速度快.

Eye localization and state analysis for driver fatigue detection

To solve the problem of eye precise localization in head multi-position,an algorithm based on skin color and texture feature is proposed. Face is detected based on skin color and according to the gray difference between eyes and other parts,and eye candidate areas are found with the method of binarization and morphological image processing. Eyes are detected by calculating the texture characteristics values of candidate areas. The method of black fleck fitting elliptic is used to check the factuality of the 2 detected eyes and measure the eye opening extent. The experimental results demonstrate the texture characteristics values of candidate areas are still different when head angle changes and the proposed method can accurately detect eyes. The method is simple and fast,and not influenced by driver head posture.