基于肤色分割和AdaBoost算法的人脸检测

Face Detection Based on Skin Color Segmentation and AdaBoost Arithmetic

针对复杂背景和可变光照下的静态彩色图像人脸检测,提出了一种基于肤色分割和AdaBoost算法的人脸检测方法。首先把彩色图像转换到YCbCr空间。接着应用自适应光线补偿算法对图像进行光线补偿。再结合形态学、几何约束等方法排除背景干扰、进行肤色区域分割。其次应用改进的AdaBoost算法对分割出的区域进行验证,进而精确定位人脸。实验表明:该方法检测率高、适应性好、鲁棒性强,对人脸检测有较强实用性。

Focused on face detection of static color image under complex background and variable illumination, a method combining adaptive light compensation and AdaBoost algorithm is proposed. First, conversion of input im- age from RGB to YCbCr, then, the algorithm worked by doing light compensation using self-adaptive compensation algorithm, and then used morphologic methods, geometric restrict to make possible face area segmented and located the candidate＇ s face area. At last used improved AdaBoost arithmetic to test and indicate. The experiments show that the method has high accuracy, good adaptability, strong robustness to face detection problem.