四川轻化工大学学报（自然科学版）2023，Vol.36Issue(6)：57-64,8.DOI:10.11863/j.suse.2023.06.08
基于CLAHE的PCA-LDA典型地域人脸识别研究
Study on Typical Regional Face Recognition Based on PCA-LDA with CLAHE
摘要
Abstract
Aiming at the problem that face characteristics of typical regions in southern and northern China are not obvious and difficult to identify,a PCA-LDA algorithm based on Contrast Limited Adaptive Histogram Equalization(CLAHE)has been proposed.Firstly,a typical regional face dataset in the south and north of China is established,and local information enhancement and noise suppression are achieved by contrast stretching after chunking the face images with using CLAHE.Then,the Principal Components Analysis(PCA)algorithm is used to map the high-dimensional face images to a low-dimensional space and generate the eigenfaces that can best reflect the regional characteristics of the sample.Subsequently,the Linear Discriminant Analysis(LDA)algorithm is used to find the best projection direction of the sample to further compress the dimensionality.Finally,the Support Vector Machines(SVM)classifier is used for recognition.The final results show that the proposed algorithm can effectively enhance face features and reduce the interference of other factors,achieving a recognition rate of 64.0% and 77.0% for typical regions in the south and north of China,respectively.关键词
PCA-LDA/地域特征/特征脸/支持向量机Key words
PCA-LDA/regional characteristics/eigenfaces/support vector machines分类
信息技术与安全科学引用本文复制引用
何李,蒋行国,李嘉利,李德才..基于CLAHE的PCA-LDA典型地域人脸识别研究[J].四川轻化工大学学报（自然科学版）,2023,36(6):57-64,8.基金项目
四川省科技厅省院省校项目(2020YFSY0027) （2020YFSY0027）
人工智能四川省重点实验室开放基金项目(2020RZJ03) （2020RZJ03）
四川轻化工大学人才引进项目(2019RC12) （2019RC12）
