基于支持向量机的人脸识别算法研究

对基于支持向量机的人脸识别算法进行了研究,并通过仿真实验验证算法的有效性.通过缩小图像的尺寸和离散余弦变换(DCT)来实现图像的预处理,应用基于类内平均脸的主成分分析(PCA)提取人脸图像的特征,应用支持向量机(SVM)实现人脸图像识别.还重点对影响人脸识别系统速度和识别准确率的相关因素进行了研究,为研究人脸识别技术的应用提供理论依据.

Face Recognition Algorithm Research Based on Support Vector Machine

This paper studies face recognition algorithm based on support vector machine, and validates the validity of the algorithm by the simulation experiment.By reducing the image size and adjusting discrete cosine transform (DCT) can realize the preprocessed image, applicating the principal component analysis (PCA) of class-based average face extraction of face image characteristics, applicating support vector machine (SVM) to implement face recognition. This paper mainly studies the impact of face recognition system on speed and the accuracy, which provides the theory basis for face recognition technology.