Title
Fast periocular authentication in handheld devices with reduced phase intensive local pattern
Abstract
To ensure highest security in handheld devices, biometric authentication has emerged as a reliable methodology. Deployment of mobile biometric authentication struggles due to computational complexity. For a fast response from a mobile biometric authentication method, it is desired that the feature extraction and matching should take least time. In this article, the periocular region captured through frontal camera of a mobile device is considered under investigation for its suitability to produce a reduced feature that takes least time for feature extraction and matching. A recently developed feature Phase Intensive Local Pattern (PILP) is subjected to reduction giving birth to a feature termed as Reduced PILP (R-PILP), which yields a matching time speed-up of 1.56 times while the vector is 20% reduced without much loss in authentication accuracy. The same is supported by experiment on four publicly available databases. The performance is also compared with one global feature: Phase Intensive Global Pattern, and three local features: Scale Invariant Feature Transform, Speeded-up Robust Features, and PILP. The amount of reduction can be varied with the requirement of the system. The amount of reduction and the performance of the system bears a trade-off. Proposed R-PILP attempts to make periocular suitable for mobile devices.
Year
DOI
Venue
2018
https://doi.org/10.1007/s11042-017-4965-6
Multimedia Tools Appl.
Keywords
Field
DocType
Fast biometric matching,Biometric on mobile device,Periocular biometric,Phase intensive local pattern,Feature reduction
Computer vision,Scale-invariant feature transform,Authentication,Software deployment,Pattern recognition,Computer science,Feature extraction,Mobile device,Artificial intelligence,Biometrics,Periocular Region,Computational complexity theory
Journal
Volume
Issue
ISSN
77
14
1380-7501
Citations 
PageRank 
References 
3
0.38
21
Authors
5
Name
Order
Citations
PageRank
Sambit Bakshi112323.10
Pankaj K. Sa2122.13
Haoxiang Wang327615.25
Soubhagya Sankar Barpanda4262.05
Banshidhar Majhi535649.76