Multi-algorithmic cancelable fingerprint template generation based on weighted sum rule and T-operators

With the emergence of biometric-based authentication systems in real-world applications, template protection in biometrics is a significant issue to be considered in the recent years. This paper presents two feature set computation algorithms, namely nearest neighbor feature set (NNFS) and Delaunay...

Full description

Saved in:
Bibliographic Details
Published in:Pattern analysis and applications : PAA 2018-05, Vol.21 (2), p.397-412
Main Authors: Sandhya, Mulagala, Prasad, Munaga V. N. K.
Format: Article
Language:English
Subjects:
Algorithms
Biometrics
Computer Science
Fingerprints
Norms
Operators
Pattern Recognition
Theoretical Advances
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:With the emergence of biometric-based authentication systems in real-world applications, template protection in biometrics is a significant issue to be considered in the recent years. This paper presents two feature set computation algorithms, namely nearest neighbor feature set (NNFS) and Delaunay triangle feature set (DTFS), for a fingerprint sample. Further, the match scores obtained from these algorithms are fused using weighted sum rule and T -operators ( T -norms and T -conorms). The experimental evaluation done on FVC 2002 databases confirms the credibility of fusion method compared to each individual algorithm used for fusing. The EER obtained for proposed method is 0 %, 0.059 %, and 3.93 % for FVC 2002 DB1, DB2, and DB3 databases, respectively. This paper also aims to prove the effectiveness of applying T -operators for fusion at score level in fingerprint template protection.
ISSN:1433-7541
1433-755X
DOI:10.1007/s10044-016-0584-5