Stroke-to-stroke matching in on-line signature verification

On-line Signature Verification is a field of verifying the time series signature data that normally obtained from the tablet-based device. Unlike common signature image, the on-line signature image data consists of points that are arranged in sequence based on time. The aim of this research is to de...

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Main Author: Ahmad Jaini, Azhar
Format: Thesis
Language:English
Published: 2010
Subjects:
Online Access:http://eprints.utm.my/11063/6/AzharAhmadJainiMFSKSM2010.pdf
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author Ahmad Jaini, Azhar
author_facet Ahmad Jaini, Azhar
author_sort Ahmad Jaini, Azhar
collection ePrints
description On-line Signature Verification is a field of verifying the time series signature data that normally obtained from the tablet-based device. Unlike common signature image, the on-line signature image data consists of points that are arranged in sequence based on time. The aim of this research is to develop a new approach to map the strokes in both test and reference signatures as well as to verify the originality of the test signatures. Current methods make use of the DTW algorithm and its variant to segment them before comparing each of its data dimension. This project suggesting a modified DTW algorithm with the proposed Missed Nodes Recovery Algorithm aims to improve the mapping performance, hence the development of stroke to stroke signature comparison is possible. This project is also proposing a method to compare the strokes with its similar strokes in on-line signature. All algorithm and experiments will be carried out using Matlab. The output of this research project is an algorithm that can be used to map strokes as well as to compare similarity of strokes in on-line signature.
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spelling utm.eprints-110632017-09-26T07:29:05Z http://eprints.utm.my/11063/ Stroke-to-stroke matching in on-line signature verification Ahmad Jaini, Azhar QA75 Electronic computers. Computer science On-line Signature Verification is a field of verifying the time series signature data that normally obtained from the tablet-based device. Unlike common signature image, the on-line signature image data consists of points that are arranged in sequence based on time. The aim of this research is to develop a new approach to map the strokes in both test and reference signatures as well as to verify the originality of the test signatures. Current methods make use of the DTW algorithm and its variant to segment them before comparing each of its data dimension. This project suggesting a modified DTW algorithm with the proposed Missed Nodes Recovery Algorithm aims to improve the mapping performance, hence the development of stroke to stroke signature comparison is possible. This project is also proposing a method to compare the strokes with its similar strokes in on-line signature. All algorithm and experiments will be carried out using Matlab. The output of this research project is an algorithm that can be used to map strokes as well as to compare similarity of strokes in on-line signature. 2010-03 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/11063/6/AzharAhmadJainiMFSKSM2010.pdf Ahmad Jaini, Azhar (2010) Stroke-to-stroke matching in on-line signature verification. Masters thesis, Universiti Teknologi Malaysia, Faculty of Computer Science and Information Systems.
spellingShingle QA75 Electronic computers. Computer science
Ahmad Jaini, Azhar
Stroke-to-stroke matching in on-line signature verification
title Stroke-to-stroke matching in on-line signature verification
title_full Stroke-to-stroke matching in on-line signature verification
title_fullStr Stroke-to-stroke matching in on-line signature verification
title_full_unstemmed Stroke-to-stroke matching in on-line signature verification
title_short Stroke-to-stroke matching in on-line signature verification
title_sort stroke to stroke matching in on line signature verification
topic QA75 Electronic computers. Computer science
url http://eprints.utm.my/11063/6/AzharAhmadJainiMFSKSM2010.pdf
work_keys_str_mv AT ahmadjainiazhar stroketostrokematchinginonlinesignatureverification