基于主成分分析的人脸个体差异识别算法

Recognition Algorithm of Face Individuality Difference Based on Principal Component Analysis

传统基于主成分分析(PCA)的人脸识别算法不能最优区分不同种类样本。为此,提出一种新的基于PCA的人脸识别算法。利用PCA降维方法提取人脸的个体差异特征,并采用最近邻距离分类器对该特征进行分类。在ORL人脸数据库上的实验结果表明,与传统算法相比,该算法的正确识别率较高。

The Principal Component Analysis（PCA） is not the best method to extract features for recognition because the difference between different kinds is not considered.Aiming at this problem,a new face recognition algorithm based on PCA is proposed.It uses PCA reducing dimensions method to extract the individuality difference.A nearest neighbor classifier is employed to classify the extracted features.The method in the paper is evaluated on the ORL face image database,a series of experiments to compare the proposed approach with traditional PCA method.Experimental results demonstrate the efficacy of the algorithm.