Caltech Vision Group Signature Data
Description
****************************************************************************
*
* Caltech Vision Group Signature Data version 1.0
* (c) Mario E. Munich & Pietro Perona
* California Institute of Technology
* Copyright 1998-2002
*
* In case that this data is used for a publication, please
* cite the following articles:
*
* @ARTICLE{munichP02,
* AUTHOR = {M.E.~Munich and P.~Perona},
* TITLE = {Visual Input for Pen Based Computers},
* JOURNAL = {IEEE Trans. Pattern Analysis and Machine Intelligence},
* YEAR = {2002},
* VOLUME = {24},
* NUMBER = {3},
* PAGES = {313--328}
* }
*
* @ARTICLE{munichP03,
* AUTHOR = {M.E.~Munich and P.~Perona},
* TITLE = {Visual Identification by Signature Tracking},
* JOURNAL = {IEEE Trans. Pattern Analysis and Machine Intelligence},
* YEAR = {2003}
* }
*
* @ARTICLE{munichP95,
* AUTHOR = {M.E.~Munich and P.~Perona},
* TITLE = {Apparatus and Method for Tracking Handwriting from Visual Input
* },
* JOURNAL = {US Patent 6,044,165},
* YEAR = {filed 6/15/1995, granted 3/28/2000}
* }
*
* Disclaimer:
* The data is provided "as is", without warranty of any kind.
* The authors shall not be liable for any damages arising
* from the use of the data.
*
* License:
* This data is free software and it is intended ONLY for academic
* purposes, no commercial use is allowed; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This data is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307,
* USA.
*
****************************************************************************
Installation:
------------
The data consists of the following:
set1 --> signatures from 56 subjects (25 signatures and 10 forgeries)
set2 --> signatures from 50 subjects (30 signatures and 10 forgeries)
The data is provided in a compressed tar ball.
Use the command:
tar -xvzf signDist1.0.tgz
and the data would be installed in its own directory signDist1.0.
The directory structure is the following:
signDist1.0 ---\
|
|--- set1 ---\
| |
| |--- listset1
| |
| |--- data ---\
| | |
| | |--- s001 ---\
| | | |
| | | |--- s001000
| | | |--- s001001
| | | |--- ...
| | | |--- s001Count
| | |
| | |--- s002 ---\
| | | |
| | | ... |
| |
| |--- forgeries ---\
| | |
| | |--- s001 ---\
| | | |
| | | |--- s001f000
| | | |--- s001f001
| | | |--- ...
| | | |--- s001fCount
| | |
| | |--- s002 ---\
| | | |
| | | ... |
|
|--- set2 ---\
| |
| |--- listset2
| |
| |--- data ---\
| | |
| | |--- s001 ---\
| | | |
| | | |--- s001000
| | | |--- s001001
| | | |--- ...
| | | |--- s001Count
| | |
| | |--- s002 ---\
| | | |
| | | ... |
| |
| |--- forgeries ---\
| | |
| | |--- s001 ---\
| | | |
| | | |--- s001f000
| | | |--- s001f001
| | | |--- ...
| | | |--- s001fCount
| | |
| | |--- s002 ---\
| | | |
| | | ... |
The listset1 and listset2 files detail the subjects that are included
in the set. Each subject has a corresponding directory for his/her
signatures and the corresponding forgeries. These directories are
called s0xx where xx is the subject number. Inside the corresponding
subject directory, there is file called s0xxCount that has the number
of signatures that are stored in the directory. The signatures are
named s0xx0yy where yy is the signature number. For the case of the
forgeries the naming convention is s0xxf0yy. The signatures are saved
in ASCII format. The first row of the file indicates the number of
samples of the signature. The second row and on is composed of two
numbers, the coordinates x and y of the corresponding sample.
You could use the provided matlab files view_subject.m,
view_signature.m, and view_forgery.m to obtain a plot of the
corresponding signatures. These functions are very simple and
rudimentary, but are enough to show the data.
Comments:
--------
* set1 and set2 were captured with a similar application one year apart from
each other.
* there is no subject repetition between the two sets.
* both sets were used in the experimental results presented in \cite{munichP03}
however, the signatures of set1 have been renamed for this distribution
(see the file set1-mapping.txt for more information).
* Most of the signatures and forgeries from set2 have a image taken when
the subject had finished writing his/her signature.
If you find this data useful for your work, please drop me a note to
mariomu@vision.caltech.edu and I will have you posted regarding
changes and improvements of the data sets.
Files
| Name | Size | Actions |
|---|---|---|
|
md5:9a0651e3f8b6948c3109a13257abc090
|
92.9 MB | Download |