Title
A robust alignment-free fingerprint hashing algorithm based on minimum distance graphs
Abstract
Abstraction of a fingerprint in the form of a hash can be used for secure authentication. The main challenge is in finding the right choice of features which remain relatively invariant to distortions such as rotation, translation and minutiae insertions and deletions, while at the same time capturing the diversity across users. In this paper, an alignment-free novel fingerprint hashing algorithm is proposed which uses a graph comprising of the inter-minutia minimum distance vectors originating from the core point as a feature set called the minimum distance graph. Matching of hashes has been implemented using a corresponding search algorithm. Based on the experiments conducted on the FVC2002-DB1a and FVC2002-DB2a databases, we obtained an equal error rate of 2.27%. The computational cost associated with our fingerprint hash generation and matching processes is relatively low, despite its success in capturing the minutia positional variations across users.
Year
DOI
Venue
2012
10.1016/j.patcog.2012.02.022
Pattern Recognition
Keywords
Field
DocType
equal error rate,inter-minutia minimum distance,robust alignment-free fingerprint,minutia positional variation,core point,fingerprint hash generation,computational cost,minimum distance graph,alignment-free novel fingerprint,main challenge,corresponding search algorithm,fingerprint,security,hash
Search algorithm,Double hashing,Pattern recognition,Minutiae,Universal hashing,Rolling hash,Artificial intelligence,Hash function,K-independent hashing,Dynamic perfect hashing,Machine learning,Mathematics
Journal
Volume
Issue
ISSN
45
9
0031-3203
Citations 
PageRank 
References 
31
0.97
17
Authors
3
Name
Order
Citations
PageRank
Priyanka Das1311.31
Kannan Karthik2406.73
Boul Chandra Garai3311.31