|
--- |
|
license: cc-by-4.0 |
|
--- |
|
|
|
extract from https://data.mendeley.com/datasets/c5mfhr2xcz/1 |
|
|
|
# Offline Handwritten Signature Database based on Age Annotation (OHSDA) |
|
|
|
Published: 27 February 2023 |
|
Version 1 |
|
DOI: 10.17632/c5mfhr2xcz.1 |
|
|
|
Contributors: |
|
Sathish Kumar , Dr Shivanand Gornale |
|
|
|
|
|
## Description |
|
Handwritten signature analysis is the endeavoring research in many verification and recognition system problem. |
|
As per our best of knowledge there is less number of publicly available datasets which have age class annotation |
|
for signature. With this motivation, own dataset is created. The nature of this own offline handwritten |
|
signature database is described below. |
|
|
|
• In-house total of 6010 signatures were collected randomly in 601 healthy volunteers (330 males; 271 females; |
|
Age range 18-50 years) |
|
|
|
• From each individual 10 signatures acquired on a white A4 paper sheet using blue or black colored ball pen. |
|
|
|
• To avoid geometrical variations, the papers with sample signatures have been scanned using the EPSON DS 1630 |
|
color scanner with a resolution of 300 DPI. |
|
|
|
• The signature samples consist of multilingual scripts of Kannada, Hindi, Marathi, and English. |
|
|
|
• The participants who had knowledge of English and other regional languages, have been educated about the |
|
purpose of collection of signature samples. |
|
|
|
Male signatures age range will start from ‘male signatures 18-50 years’ and female signature will starts from |
|
‘female signatures 18-50 years’. |
|
|
|
All Scanned Offline Signature samples are in .jpg format, the male signatures start with 'm' and female |
|
signatures start with 'f'. |
|
|
|
|
|
|
|
Download All 109 MB |
|
|
|
Files |
|
|
|
Female Signatures 18-50 years |
|
|
|
Male Signatures 18-50 years |
|
Steps to reproduce |
|
Handwritten signatures are socially and legally accepted behavioral biometric data for authenticating the |
|
documents like letters, contracts, wills, MOU’s, etc. for validation in day to day life. |
|
|
|
However, it is observed that very less effort is done on age identification based on offline handwritten |
|
signatures. These signatures contain multilingual texts. Therefore, to bridge this research gap, the proposed |
|
database is used to identify writer’s age group from handwritten signatures of individuals. |
|
|
|
The signature samples were collected from various educational institutions and some village are for diversity |
|
purpose. |
|
|
|
• In-house total of 6010 signatures were collected randomly in 601 healthy volunteers (330 males; 271 females; |
|
Age range 18-50 years) |
|
|
|
• From each individual 10 signatures acquired on a white A4 paper sheet using blue or black colored ball pen. |
|
|
|
• To avoid geometrical variations, the papers with sample signatures have been scanned using the EPSON DS 1630 |
|
color scanner with a resolution of 300 DPI. |
|
|
|
• The signature samples consist of multilingual scripts of Kannada, Hindi, Marathi, and English. |
|
|
|
• The participants who had knowledge of English and other regional languages, have been educated about the |
|
purpose of collection of signature samples. |
|
|
|
All participants gave written informed consent, and the study was approved by the institutional ethics |
|
committee. |
|
|
|
|
|
Institutions |
|
Rani Channamma University |
|
Categories |
|
Biometrics, Age Diversity |
|
|
