为了解决二维人脸识别受环境光干扰,三维人脸识别依赖标定数据的问题,提出了一种基于相位测量轮廓术的人脸识别方法。首先使用相位测量轮廓术获得人脸的相位和反射率数据,相位图中暗含了人脸区域的三维信息,反射率图也排除了环境光的干扰,它们经过规范化后均可以直接使用传统二维识别方法进行人脸识别。在实验中,使用了主成分分析法和最近邻分类器进行人脸识别。实验结果表明,这种方法对人脸识别是有效的,对比二维灰度图和三维深度图有更好的识别效果。
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.