LBP based biometrie identification using the periocular region

Biometrie systems have become a vital part of our present day automated systems. Every individual has its unique biometrie features in terms of Face, Iris and periocular regions. Identification/Recognition of a person by using these biometrie features is significantly studied over the last decade to build robust systems. The periocular region has become the powerful alternative for unconstrained biometrics with better robustness and high discrimination ability. In the proposed paper local descriptor Local Binary Patterns (LBP), is used for the feature extraction of discriminative features from the regions of full face, periocular and city block distance is used as a classifier. FRGC and FERET databases are utilized for the experimentation to compare the performance of both periocular and face biometric modalities and it showed that the periocular region has a similar level of performance of the face region using only 25% data of the complete face.