Comparison of signature on paper and apple® ipad using multivariate analysis
The transformation of documentation either in legal public or private industry had moved with the digitalization of business around the world in an unpredicted acceleration in last two decades particularly since the Covid-19 pandemic. The Forensic Document Examiners (FDEs) for this study was on h...
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Main Author: | |
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Format: | Thesis |
Language: | English |
Published: |
2022
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Subjects: | |
Online Access: | http://eprints.usm.my/58453/1/LIM%20SUE%20XIAN-24%20pages.pdf |
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Summary: | The transformation of documentation either in legal public or private industry
had moved with the digitalization of business around the world in an unpredicted
acceleration in last two decades particularly since the Covid-19 pandemic. The
Forensic Document Examiners (FDEs) for this study was on high demand to move
forward toward digital document examination just like the way they did for
conventional physical document examination. Signature, being one of the most
socially acceptable biometric traits for the past centuries, has become one of the
challenges when a handwritten signature was digitally captured on digital device
instead of the traditional paper as writing medium. Most of the previously available
research focused on the temporal digital data for the features and characteristics of
handwritten signatures. This study aimed to focus on the height ratio analysis of
writing zones in handwritten signatures deposited on paper medium and on the Apple®
iPad medium when both were treated as static flat images when the digital document
was not made available to the FDE. The results indicated that there were differences
for signatures on different writing mediums as opposed to the principle of handwriting
that the writing zone of a person remained relatively uniform in most of the aspects.
The implementation of statistical approaches allowed the handwriting examination
being presented in quantitative and objective opinions to the court of law by using
%RSD, the k-means clustering, and factor analysis as preliminary study. |
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