A new method of face recognition, which is based on phase measuring profilometry, is proposed to solve the problems of the ambient light influence in 2-D face recognition and the dependence on calibration data in 3-D face recognition. Firstly, the phase information and reflectivity information of face are obtained based on phase measuring profilometry. The phase image contains 3-D information and the reflectivity image is immune to the ambient light. Then the traditional 2-D face recognition approaches can be used after normalization. In experiments, principal component analysis and nearest neighbor method are used to classify the face. Experiment results show the effectiveness of the proposed method, which achieves higher recognition accuracy than that achieved by using grayscale image and range image.