Abstract: This paper presents a fast algorithm for detecting facial parts such as nose，eyes and lips in an image by using lifting dyadic wavelet transform.Free parameters in the lifting filters are learned so as to maximize the cosine of an angle between a vector whose components are the lifting filters and a vector of pixels in the facial part.Applying the learned filter to a test image，facial parts in the image can be detected.The experimental results indicate that the approach is high robust，and it is fit to solve the problem of face detection in complex background.Because of the algorithm’s simpleness，it can be easily achieved by hardware，and this will shorten the time consuming on face detection.This made it possible to detect faces in real time.So it has wide application perspective at fields of visual telephone，intelligent monitor etc.

Key words: dyadic wavelet transform, lifting dyadic wavelet filters, face feature extraction, face detection

摘要： 提出一种基于提升二进小波变换的检测人脸部位（如鼻子、眼睛和嘴唇等）的快速算法。在提升二进小波滤波器中的自由参数是学习的，从便使两个向量（其中一个向量的分量是提升二进小波滤波器系数，另一个向量的分量是人脸某部位像素）之间的夹角的余弦值最大化。学习得到的滤波器应用到测试图像中，可以检测人脸某些部位。实验结果表明，该方法具有较强的鲁棒性，能够很好地解决复杂背景下的人脸检测问题。由于该方法实现的简单性，并容易由硬件实现，使得检测速度进一步提高，因此该方法在可视电话等领域有着广阔的应用前景。

关键词: 二进小波变换, 提升二进小波滤波器, 人脸特征提取, 人脸检测