Facial features are the most natural and direct biological features. They are direct, friendly, convenient, and easy for users to accept. Face recognition has become the most active research field in image processing, pattern recognition, and computer vision due to its wide potential applications in monitoring, criminal identification, and human-computer interaction. Linear discriminant analysis is one of the most classic and widely used methods in feature extraction. In recent years, how to extract Fisher optimal discriminant features in small sample conditions has been a concern for many researchers. This paper describes the application of Fisher discriminant method in the classification of face image samples. The experimental results simulated on the standard database ORL face database and Yale face database confirm the effectiveness and stability of the method.
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