1[摘要] 当今社会越来越重视个人身份信息的安全性，然而，当处于信息化环境下，个人的身份信息将会被数据化，并将被网络隐藏起来。现如今，如何持续优化现有的识别技术，已经成为全球信息化领域亟待解决的根本问题。近年来，各种类型的计算机技术逐步获得相对稳定的蓬勃发展，多样化生物识别技术应运而生，在此背景下，人脸以及虹膜等一系列生物学特征，均日益充斥于信息安全认证领域。从本质上而言，以生物识别技术为基础而成功研究出的信息安全验证技术，将会在未来一段时期逐步实现商业化，并将替代以 ID 验证为主的识别方法。在此之中，面部识别显得尤为关键，正是由于面部所表现出的独特性，隐藏性和简洁性，所以更加的容易被认可。若运用此类方式，将可有效提高人脸识别的工作效率。在本篇论文中，旨在针对以 PCA 为基础而成功构建的特征提取方法，进行科学合理的综合研究，并提出一种 PCA 人脸识别算法。[关键词]：人脸识别，特征提取，PCAAbstract: Today's society pays more and more attention to the security of personal identity information. However, when it is in an information environment, personal identity information will be digitized and will be hidden by the network. Nowadays, how to continuously optimize existing identification technologies has become a fundamental problem to be solved urgently in the field of informationization in the world. In recent years, various types of computer technology have gradually gained relatively stable and vigorous development, and diverse biometric identification technologies have emerged. In this context, a series of biological features such as human face and iris are increasingly filled in the field of information security certification. . In essence, the information security verification technology successfully developed based on biometric technology will be gradually commercialized in the future, and will replace the identification method based on ID verification. Among them, facial recognition is particularly important, and it i...
