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Forensic analysis of offline signature using multi-layer perception and random forest

Forensic applications having great importance in the digital era, for the investigation of different types of crimes. The forensic analysis includes Deoxyribonucleic Acid (DNA) test, crime scene video and images,, forged documents analysis, computer-based data recovery, fingerprint identifications,...

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Main Authors: Shah, Abdul Salam, Shah, Masood, Fayaz, Muhammad, Wahid, Fazli, Khan, Hira Khalid, Shah, Asadullah
Format: Article
Language:English
Published: Science & Engineering Research Support soCiety (SERSC) 2017
Subjects:
T10.5 Communication of technical information
Online Access:http://irep.iium.edu.my/56182/1/13-Forensic-Analysis-of-Offline-Signatures-using-Multilayer.pdf
http://irep.iium.edu.my/56182/
http://www.sersc.org/journals/IJDTA/vol10_no1.php
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spelling my.iium.irep.561822017-04-15T07:12:21Z http://irep.iium.edu.my/56182/ Forensic analysis of offline signature using multi-layer perception and random forest Shah, Abdul Salam Shah, Masood Fayaz, Muhammad Wahid, Fazli Khan, Hira Khalid Shah, Asadullah T10.5 Communication of technical information Forensic applications having great importance in the digital era, for the investigation of different types of crimes. The forensic analysis includes Deoxyribonucleic Acid (DNA) test, crime scene video and images,, forged documents analysis, computer-based data recovery, fingerprint identifications, handwritten signature verification and facial recognition. The signatures are divided into two types i.e. genuine and forgery. The forgery signature can lead to the huge amount of financial losses and create other legal issues as well. The process of forensic investigation for the verification of genune signature and detection of forgery signature in law related departements has been manula and the same can be automated using digital image processing techniques, and automated forensic signature verificatiob applications. The signatures represent any person's authority to the forged signature may also be used in a crime. Research has been done to automate the forensic investigation process, but due to the internal verification of signatures, the automation of signature verification still remains a challenging problem for researchers. In this paper, we have further extended previous research carried out in [1-2] and proposed a Forensic signature verification model based on two classifiers i.e. Multi-layer Perception (MLP) and Random Forest for the classification of genuine and forgery signatures. Science & Engineering Research Support soCiety (SERSC) 2017 Article REM application/pdf en http://irep.iium.edu.my/56182/1/13-Forensic-Analysis-of-Offline-Signatures-using-Multilayer.pdf Shah, Abdul Salam and Shah, Masood and Fayaz, Muhammad and Wahid, Fazli and Khan, Hira Khalid and Shah, Asadullah (2017) Forensic analysis of offline signature using multi-layer perception and random forest. International Journal of Database Theory and Applications, 10 (1). pp. 139-148. ISSN 2005-4270 http://www.sersc.org/journals/IJDTA/vol10_no1.php 10.14257/ijdta.2017.10.1.13
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic T10.5 Communication of technical information
spellingShingle T10.5 Communication of technical information
Shah, Abdul Salam
Shah, Masood
Fayaz, Muhammad
Wahid, Fazli
Khan, Hira Khalid
Shah, Asadullah
Forensic analysis of offline signature using multi-layer perception and random forest
description Forensic applications having great importance in the digital era, for the investigation of different types of crimes. The forensic analysis includes Deoxyribonucleic Acid (DNA) test, crime scene video and images,, forged documents analysis, computer-based data recovery, fingerprint identifications, handwritten signature verification and facial recognition. The signatures are divided into two types i.e. genuine and forgery. The forgery signature can lead to the huge amount of financial losses and create other legal issues as well. The process of forensic investigation for the verification of genune signature and detection of forgery signature in law related departements has been manula and the same can be automated using digital image processing techniques, and automated forensic signature verificatiob applications. The signatures represent any person's authority to the forged signature may also be used in a crime. Research has been done to automate the forensic investigation process, but due to the internal verification of signatures, the automation of signature verification still remains a challenging problem for researchers. In this paper, we have further extended previous research carried out in [1-2] and proposed a Forensic signature verification model based on two classifiers i.e. Multi-layer Perception (MLP) and Random Forest for the classification of genuine and forgery signatures.
format Article
author Shah, Abdul Salam
Shah, Masood
Fayaz, Muhammad
Wahid, Fazli
Khan, Hira Khalid
Shah, Asadullah
author_facet Shah, Abdul Salam
Shah, Masood
Fayaz, Muhammad
Wahid, Fazli
Khan, Hira Khalid
Shah, Asadullah
author_sort Shah, Abdul Salam
title Forensic analysis of offline signature using multi-layer perception and random forest
title_short Forensic analysis of offline signature using multi-layer perception and random forest
title_full Forensic analysis of offline signature using multi-layer perception and random forest
title_fullStr Forensic analysis of offline signature using multi-layer perception and random forest
title_full_unstemmed Forensic analysis of offline signature using multi-layer perception and random forest
title_sort forensic analysis of offline signature using multi-layer perception and random forest
publisher Science & Engineering Research Support soCiety (SERSC)
publishDate 2017
url http://irep.iium.edu.my/56182/1/13-Forensic-Analysis-of-Offline-Signatures-using-Multilayer.pdf
http://irep.iium.edu.my/56182/
http://www.sersc.org/journals/IJDTA/vol10_no1.php
_version_ 1643614870336176128
score 13.211869

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