Open AccessDesign of Face QR Code Recognition System based on PCA
Author(s) -
Tan Liu,
Fengzhi Wu,
Qing Wang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1944/1/012020
Subject(s) - facial recognition system , dimensionality reduction , computer science , principal component analysis , face (sociological concept) , artificial intelligence , code (set theory) , dimension (graph theory) , pattern recognition (psychology) , curse of dimensionality , decoding methods , encoding (memory) , encode , set (abstract data type) , process (computing) , computer vision , algorithm , mathematics , social science , biochemistry , chemistry , sociology , pure mathematics , gene , programming language , operating system
This article discusses the face two-dimensional code recognition technology, using the PCA algorithm to study the dimensionality reduction processing process of the face image. Based on the analysis of QR encoding and decoding methods, the generation of face two-dimensional codes is realized. Choose 140 pictures in ORL face database as the experimental data set, study the face two-dimensional code recognition system, and realize a process of face recognition. The experimental results show that the face image data has a large dimension, and the principal component analysis method can be used to obtain the key data. Through the experiment, PCA can be used to reduce the dimensionality to obtain the effective information of the face, and to encode and decode the two-dimensional code. The ZXing two-dimensional code open source library called by the experiment has high experimental efficiency, which is beneficial to improve the operating efficiency of face two-dimensional code recognition and facilitate the machine to complete the simulation.