Abstract:
The use of biometrics is evolving day by day in our society. Fingerprint recognition is
well known for its high acceptability and popularity in the world of biometric systems.
Fingerprint recognition has its applications in many fields such as banking, medical
and insurance industry, police department, database management systems, identity
authentication, police department, border security and many other areas. There are
different methods and techniques used for matching fingerprints but the most common
and popular approach is minutiae based matching. Our approach is based on
structural matching and the matching algorithm presented here is the improved and
modified form of [1]. In this method, matching is done on the basis of five closest
neighbors of one single minutia that is also called a center minutia. An authentication
of minutia is based on these surrounding neighbors. The approach we present here is
divided in to two stages, first stage performs initial filtration and the second stage
includes special matching criteria that incorporate fuzzy logic as well as a novel
feature to select final minutiae for matching score calculation. The method of
selecting center point for second stage is also adopted. This algorithm is able to
perform well for translated, rotated and stretched fingerprints and does not require
any process for alignment before matching. Two error rates (FAR and FRR) are used
to represent the performance of an algorithm. Tests have been carried out on the
standard database FVC 2002 (DB1_A) using P-IV (1.8MHz) with 512MB of RAM.
MALAB 7.0 has been used for the implementation of proposed algorithm.
Experimental results show that algorithm is fast, efficient and reliable.
