Affiliations: [a] College of Computer Science and Engineering, Chongqing Three Gorges University, Chongqing, China | [b] College of Electronic and Information Engineering, Chongqing Three Gorges University, Chongqing, China
Correspondence:
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Corresponding author: Weijian Fang, College of Computer Science and Engineering, Chongqing Three Gorges University, Chongqing, China. E-mail: [email protected].
Abstract: Facial recognition is a technique for biometric identification, generally applied to finance, cybersecurity, public security, property management, and other important management departments. In this paper, the facial recognition system based on improved LBP and PCA mathematical algorithm is used to extract the relationship between the facial centre point and other phase domain points. After using PCA to reduce the dimension, the facial features are obtained. The facial recognition system designed by the thesis covers face image creation, face image pre-processing, face image recognition and result output module. Studies have shown that the system’s face recognition accuracy can be as high as 90%.
Keywords: Feature extraction, principal component analysis, dimensionality reduction, recognition rate
