摘要
This paper uses principal component analysis （PCA） to train the face and extract the characteristic value. This approach achieves the purpose of rapid attendance. PCA is an early and important approach for face recognization. It can reduce the dimension of face image space as well as describe the variation characteristics between different face images. The attendance system is a realtime system that requires shorter response time, for which PCA is a best choice. We use histogram equalization to eliminate the noise and improve the performance. With convenient MATLAB GUI visual operation interface, users can click on the corresponding button to implement face recognition tasks.
This paper uses principal component analysis （PCA） to train the face and extract the characteristic value. This approach achieves the purpose of rapid attendance. PCA is an early and important approach for face recognization. It can reduce the dimension of face image space as well as describe the variation characteristics between different face images. The attendance system is a realtime system that requires shorter response time, for which PCA is a best choice. We use histogram equalization to eliminate the noise and improve the performance. With convenient MATLAB GUI visual operation interface, users can click on the corresponding button to implement face recognition tasks.
基金
Supported by Higher School Science and Technology Innovation Fund Project(2013160)
Changzhi College Teaching Reform Fund Project(JY201503)
