复杂背景下人脸检测的数学形态学运算方法

皮肤的颜色特性被广泛地应用于人脸检测和跟踪中，本文采用HSV空间与归一化RGB空间相结合的肤色模型，提取原始图像中的类肤色区域作为候选人脸目标；采用数学形态学算子，分别用来完成去除噪声和干扰，分离侯选目标，提取眼睛嘴巴孔洞，以及标示人脸轮廓等处理过程。大量实验表明，该方法能有效地剔除臂和手等非人脸肤色目标；能克服人脸遮挡，姿势和方向变化，大小差异，光照变化等造成的困难；该方法的计算开销较小，易于实现，适合快速人脸检测。

Mathematical Morphology Appoach to Face Detection in Complex Background

Skin color character is widely used for face detection and face tracking. This paper construct a mixed model in both normalized RGB and HSV color space, which can be used to acquire possible skin regions in original image. It designs a sequential flexible morphology operators which can respectively eliminate noises and disturbances, separate face candidates, acquire eye and mouth "hole", and gain contours of faces. The experimental results show that the proposed approach can not only effectively eliminate human hands and arms non-face objects in image, but also smooth away difficulties of face occlusion, pose and orientation, size difference and light variety. Furthermore, this approach is easy to implement, and its computational spending is relatively smaller. So it is suitable to fast face detection.