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Abstract:
Signature verification is a technology that can solve security problems in o ur networked
society. A new improved offline signature verification scheme is propo sed 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 d iscriminates 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.
Key words:
Offline signature, geometric centre, feature point, forgeries, euclidean distance model,
FAR (False Acceptance Rate), FRR (False Rejection Rate).
INTRODUCTION
A signature verification system and the techniques
using to solve this problem can be divided into two
classes: online and off-line
. In an online system,
Signature verification is an important research area
signature d ata can be obtained from an electronic tablet
in the field of personal authenticatio n. The recognition
of human handwriting is important concerning about
and in this case, dynamic information about writing
the improvement of the interface between human-
activity such as speed of writing, pressure applied,numbers of strokes are availab le
. In off-line systems,beings and computers
. If the computer is intelligent
enough to understand human handwriting it will
signatures written on study as has been do ne
traditionally are converted to electronic form with the
provide a more attractive and economic man-computer
help of a camera or a scanner and obviously, the
interface. In this area signature is a special case that
provides secure means for authentication, attestation
dynamic information is not available. In general, the
authorization in many high security environment. The
dynamic information represents the main writing style
of a person. Since the volume of information available
objective of the signature verification system is to
discriminate between two classes: the o riginal and the
is less, the signature verification using off-line techniques is relatively more difficult forgery, which are related to intra and interpersonal
Our work is concerned with the techniq ues of off-
variability
. The variation amon g sig natures of same
person is called Intra Personal Variation. The variation
line signature verification. The static information
between o riginals and forgeries is called Inter Personal
derived in an off-line signature verification system may
be global, structural, geometric or statistical. We
Variation.
Signature verificatio n is so different with the
concern with offline signatu re verification which is
based on geometric centre and is useful in separating
character recognition, because signature is o ften
skilled forgeries from the originals. The algorithms
unreadable and it seems it is just an image with some
particular curves that represent the writing style of the
used have given improved results as compared to the
person. Signature is just a special case of handwriting
previously proposed algorithms based on the geo metric
centre.
and often is just a symbol. So it is wisdo m and
necessary to just deal with a sig nature as a complete
Types of Forgeries:
There are three different types of
image with special distribution o f pixels and
forgeries to take into account. First one is random
representing a particular writing style and not as a
collection of letters and words
forgery which is written by the person who doesn’t