Research and Implementation of PCA Face Recognition Algorithm Based on Matlab
Shandong Agriculture and Engineering University, Jinan, Shandong, China
* Corresponding author: firstname.lastname@example.org
This paper researches the theory of PCA (Principle Component Analysis) algorithm and the feature extraction elements in the process of face recognition, summarizes application procedures of PCA algorithm in the process face recognition, and realizes the application of PCA algorithm in the process face recognition in the matlab software. The research content and realization results show that: PCA algorithm is a kind of algorithm which is very suitable for programming and realization of matlab software; the key factor to realize PCA algorithm is the selection of the number of feature vectors, which affects the recognition rate and training time of the space sample subset. The higher recognition rate indicates better results in the algorithm implementation; the shorter training time of the space sample subset indicates more excellent algorithm implementation. In the process of selection of the number of feature vectors, on one hand, there is a need to protect the recognition rate; on the other hand, there is a need to control training time of the space sample subset, in which the recognition rate is a rigid target. The shortest training time of the subset of samples is selected on the premise of meeting the recognition rate.
Key words: PCA algorithm / face recognition / training time / recognition rate / matlab realization
© Owned by the authors, published by EDP Sciences, 2015
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