Periocular Region Based Biometric Identification Using SIFT and SURF Key Point Descriptors
Kishore Kumar Kamarajugadda, Movva Pavani · 2019
In the proposed paper the discriminative capability of the periocular region of the face area is exploited in designing a robust biometric system. A periocular region-based biometric system is emerging as a better alternative for the unconstrained and uncontrolled environments. In the projected work the two key point descriptors Speeded Up Robust Features (SURF) and Scale Invariant Feature Transform (SIFT) are employed for deriving the distinctive characteristics from the periocular and complete face portions. City Block Distance method is used to compare the two feature vectors obtained from the SURF and SIFT methods. FERET and FRGC databases are used to estimate the merits of both face and periocular biometric methods. By utilizing only 25% of entire face, periocular area-based biometric systems provided almost the similar performance equivalent to the face biometric systems.