基于PCA算法的人脸识别研究

介绍了PCA算法及其在人脸识别中的应用。PCA算法是一种基于统计的算法，其优点是识别率高，速度快。基于PCA算法的特征脸方法首先根据人脸数据库训练出一系列的特征脸，然后把人脸数据库中的每个人脸图片进行映射，得出每个人的特征系数，这组系数可以表示该张图片。最后计算出待识别样本的特征系数，并与人脸数据库中的特征系数一一进行比较，以距离相近的作为识别结果。

Study of Face Recognition Based on Principal Component Analysis Method

In this paper, PCA algorithm and its application in face recognition are presented. PCA algorithm is based on the statistics, and the advantage of this algorithm is the high rate of speed and precision to identify. The EnginFace method base on PCA trains firstly the faces database to obtain the EnginFaee, and then maps every face image in the database to the EnginFaee and works out the coefficient of everyone. The coefficient can represent that face image. At last, it calculates the coefficient of the sample to be identified, and compares it with every coefficient in the face database, the nearest is the result.