基于离散余弦变换和支持向量机的人脸识别算法

提出了一种基于DCT提取人脸特征技术和支持向量机分类模型的人脸识别方法。利用离散余弦变换可提取人脸可识别的大部分信息，而支持向量机作为分类器，在处理小样本、高维数等方面具有独特的优势，且泛化能力很强，无需先验知识。从ORT人脸库上的实验结果可以看出，DCT特征提取是很有效的，且SVM的分类性能优于最近邻分类器，同时提高了整个系统的运算速度。

Face Recognition Based on DCT and Support Vector Machines

A new algorithm is presented for face recognition based on DCT and a multi-class support vector machine (SVM) model. The extracted features from human face images by DCT have major information that can be recognized. As a classifier, the SVM has its particular advantage in tackling small sample size, high dimension and etc., and is of high generalization and without need of priori knowledge. The results on ORL face database show that the DCT feature extraction method is effective and the SVM is superior to the nearest neighbor classifier in classification performance with the efficiency of the whole system improved.