This paper focuses on a software framework to support face recognition, a specific area of image processing. For the processing approach, we use principal component analysis (PCA), a data dimensionality reduction approach. The goal of this study is to understand the entire face recognition process with PCA and to present a software framework supporting multiple variations, which can be used to help users create customized face recognition applications efficiently.
['Peng Peng', 'Paulo S. C. Alencar', 'Donald D. Cowan']
A Software Framework for PCa-Based Face Recognition