基于局部特征提取的人脸识别方法的优化研究

Research on Optimization of Face Recognition Method Based on Local Feature Extraction

在现代生物技术研发和升级中,人脸识别技术作为生物识别技术中的重要组成部分,目前已经被广泛应用于金融、公共安全、人像分割以及身份鉴别等领域。在人脸特征提取中,局部特征提取环节十分关键,而提取质量很容易受遮挡、光照等因素影响。为进一步提升人脸局部特征提取的质量,本文围绕LBP、Gabor两种算法展开分析,并分别探讨了两种识别算法的操作过程。

In the development and upgrading of modern biotechnology,face recognition technology,as an important component of biometrics,has been widely used in finance,public security,portrait segmentation,identity authentication and other fields.In face feature extraction,local feature extraction is very important,and the extraction quality is easily affected by occlusion,lighting and other factors.In order to further improve the quality of face local feature extraction,this paper focuses on LBP and Gabor,and discusses the operation process of the two recognition algorithms respectively.