Face recognition is one of the most frequently used biometrics both in commercial and law enforcement applications. The individuality of facial recognition from other biometric techniques is that it can be used for surveillance purposes; as in searching for wanted criminals, suspected terrorists, and missing children. The steps in a face recognition steps are preprocessing (image enhancement), feature extraction and finally recognition. This paper identifies techniques in each step of the recognition process to improve the overall performance of face recognition. The proposed face recognition model combines enhanced 2DPCA algorithm, LDA, ICA with wavelet packets and curvelets and experimental results proves that the combination of these techniques increases the efficiency of the recognition process and improves the existing systems.
Comments: 11 Pages.
[v1] 2014-05-07 01:38:30
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