Slap image based verification system are highly secure and can be made more robust if a user's template represents all potential intra-class variations. In this paper, a template updation algorithm has been presented which helps to handle the problem of the temporal template aging and tries to capture pose variation. This uses the matched samples which are detected during slap image verification, to update the template. The proposed algorithm has been tested on challenging slap images. It shows that verification accuracy has been increased by more than 3.5% if the proposed template updation algorithm is incorporated in the verification system.
INTELLIGENT COMPUTING THEORY
Biometric template updation, Slap image verification, co-updation, Supertemplate Introduction
Pattern recognition,Computer science,Image based,Fingerprint,Artificial intelligence,Verification system