Volume 9, Issue 1 (January 2022), Pages: 99-109

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 Original Research Paper

 Title: An integrated approach on verification of signatures using multiple classifiers (SVM and Decision Tree): A multi-classification approach

 Author(s): Upasna Jindal ¹, Surjeet Dalal ^1, *, G. Rajesh ², Najm Us Sama ³, N. Z. Jhanjhi ⁴, Mamoona Humayun ⁵

 Affiliation(s):

 ¹Department of CSE, SRM University, Delhi-NCR, Sonipat, Haryana, India
 ²Department of IT, MIT Campus, Anna University, Chennai, Tamil Nadu, India
 ³Department of Science, Deanship of Common First Year, Jouf University, Sakaka, Saudi Arabia
 ⁴School of Computer Science and Engineering, SCE, Taylors University, Jaya, Malaysia
 ⁵Department of Information Systems, College of Computer and Information Sciences, Jouf University, Sakakah, Saudi Arabia

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 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0002-4325-9237

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2022.01.012

 Abstract:

A signature is a handwritten representation that is commonly used to validate and recognize the writer individually. An automated verification system is mandatory to verify the identity. The signature essentially displays a variety of dynamics and the static characteristics differ with time and place. Many scientists have already found different algorithms to boost the signature verification system function extraction point. The paper is aimed at multiplying two different ways to solve the problem in digital, manual, or some other means of verifying signatures. The various characteristics of the signature were found through the most adequately implemented methods of machine learning (support vector and decision tree). In addition, the characteristics were listed after measuring the effects. An experiment was performed in various language databases. More precision was obtained from the feature. 

 © 2021 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Online, Offline, Feature extraction, Database, Classifiers, Local and global

 Article History: Received 17 November 2020, Received in revised form 11 February 2021, Accepted 15 November 2021

 Acknowledgment 

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Jindal U, Dalal S, and Rajesh G et al. (2022). An integrated approach on verification of signatures using multiple classifiers (SVM and Decision Tree): A multi-classification approach. International Journal of Advanced and Applied Sciences, 9(1): 99-109

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 Figures

 Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7 Fig. 8 Fig. 9 Fig. 10 Fig. 11 Fig. 12 

 Tables

 Table 1 Table 2 Table 3 Table 4   

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