A Comparison of Methods for Face Recognition Systems
Chen-Hui Kuo, Li‐Chun Lai · 2012
In this paper, we propose a comparison of DCT and DWT methods for feature selection, also comparison of SVM and HMM methods for facial classifiers. We used two scan methods, top-bottom and raster scan, on purpose for data scan and then to compare the performance of two scan method. The DCT and DWT are used to frequency domain analysis to reduce the feature dimension. Nevertheless, we prove that they are the same result if apply our extract feature method. SVM was originally designed for linear binary classification. Our experiments use one-against-one method for multi-class classification because it's more suitable for practical use than the method of one-against-all. HMM has been applied with success in speech recognition. This paper reports on a comparison of the two classifiers in facial recognition. We have tested two classifiers on the ORL facial database.