Open AccessImproved Offline Signature Verification Scheme Using Feature Point Extraction Method
Author(s) -
Debashisha Jena,
Banshidhar Majhi,
Sanjay Kumar Jena
Publication year - 2008
Publication title -
journal of computer sciences/journal of computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.161
H-Index - 28
eISSN - 1552-6607
pISSN - 1549-3636
DOI - 10.3844/jcssp.2008.111.116
Subject(s) - computer science , signature (topology) , feature (linguistics) , scheme (mathematics) , feature extraction , pattern recognition (psychology) , data mining , point (geometry) , artificial intelligence , mathematics , mathematical analysis , philosophy , linguistics , geometry
Signature verification is a technology that can solve security problems in our networked society. A new improved offline signature verification scheme is proposed which is based on selecting 60 feature points from the geometric centre of the signature and compares them with the already trained feature points. The classification of the feature points utilizes statistical parameters like mean and variance. The suggested scheme discriminates between two types of originals and forged signatures. The method takes care of skill, simple and random forgeries. The objective is to reduce the two vital parameters-False Acceptance Rate (FAR) and False Rejection Rate (FRR) which are normally used in any signature verification scheme. Comparative analysis has been made with standard existing schemes