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There exist a number of biometrics methods today e.g.
Signatures, Fingerprints, Iris etc. There is considerable
interest in authentication based on handwritten signature
verification system as it is the cheapest way to
authenticate the person. Fingerprints and Iris verification
require the installation of costly equipments and hence
can not be used at day to day places like Banks etc.
As because Forensic experts can not be employed at
every place, there has been considerable effort towards
developing algorithms that could verify and authenticate
the individual’s identity . Many times the signatures are
not even readable by human beings. Therefore a signature
is treated as an image carrying a certain pattern of pixels
that pertains to a specific individual. Signature Verification
Problem therefore is concerned with determining
whether a particular signature truly belongs to a person
or not.
Signatures are a special case of handwriting in which
special characters and flourishes are viable. Signature
Verification is a difficult pattern recognition problem
as because no two genuine signatures of a person are
precisely the same. Its difficulty also stems from the fact
that skilled forgeries follow the genuine pattern unlike
fingerprints or irises where fingerprints or irises from
two different persons vary widely. Ideally interpersonal
variations should be much more than the intrapersonal
variations. Therefore it is very important to identify
and extract those features which minimize intrapersonal
variation and maximize interpersonal variations.
There are two approaches to signature verification, online
and offline differentiated by the way data is acquired. In
offline case signature is obtained on a piece of paper and
later scanned. While in online case signature is obtained
on an electronic tablet and pen. Obviously dynamic
information like speed, pressure is lost in offline case
unlike online case.
Code has been tested using Off line signature database, Grupo de Procesado Digital de Señales,
available at http://www.gpds.ulpgc.es/download/index.htm.
Index Terms: Matlab, source, code, signature recognition, off-line, on-line, verification, identification.
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Figure 1. Signature |
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A simple and effective source code for Off-Line Signature Recognition. |
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Demo code (protected
P-files) available for performance evaluation. Matlab Image Processing Toolbox is required. |
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Release |
Date |
Major features |
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1.0 |
2008.04.13 |
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We recommend to check the secure connection to PayPal, in order to avoid any fraud. This donation has to be considered an encouragement to improve the code itself. |
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Signature Recognition System - Click here for
your donation. In order to obtain the source code you
have to pay a little sum of money: 120 EUROS (less
than 168 U.S. Dollars). |
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Once you have done this, please email us luigi.rosa@tiscali.it As soon as possible (in a few days) you will receive our new release of Signature Recognition System. Alternatively, you can bestow using our banking coordinates:
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The authors have no relationship or partnership
with The Mathworks. All the code provided is written in Matlab
language (M-files and/or M-functions), with no dll or other
protected parts of code (P-files or executables). The code was
developed with Matlab 2006a. Matlab Image Processing Toolbox is required.
The code provided has to be considered "as is" and it is without any kind of warranty. The
authors deny any kind of warranty concerning the code as well
as any kind of responsibility for problems and damages which may
be caused by the use of the code itself including all parts of
the source code.
