Enhanced Face Recognition based on PCA and SVM

Feature Extraction and classification are important aspects of pattern recognition, computer vision. Principal Component Analysis is a well-known feature extraction and data representation technique. But this method is affected by illumination conditions. The combination o PCA an SVM for face recognition is presented in this paper. Before applying Principal Component Analysis preprocessing o images done by using wavelet transform. After PCA is applied or feature extraction. Support Vector Machine is used or classification. Experiments based on using Indian face database. The new technique achieves better performance than using PCA only.