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
Unique-IP document downloads: 160 times
Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.