Signature Verification Using CNN with Information Retrieval

Authors

  • Utkarsh Shukla  Department of Computer Science and Engineering, Shri Ramswaroop Memorial College of Engineering and Management, Lucknow, Uttar Pradesh, India
  • Srishti Verma  Department of Computer Science and Engineering, Shri Ramswaroop Memorial College of Engineering and Management, Lucknow, Uttar Pradesh, India
  • Tushar Gwal  Department of Computer Science and Engineering, Shri Ramswaroop Memorial College of Engineering and Management, Lucknow, Uttar Pradesh, India
  • Atul Kumar Verma  Department of Computer Science and Engineering, Shri Ramswaroop Memorial College of Engineering and Management, Lucknow, Uttar Pradesh, India

Keywords:

Signature Verification, Pattern Recognition, Image Processing, CNN

Abstract

When it comes to information security, biometric systems play a significant role in it. Signature verification is a popular research area in field of pattern recognition and image processing. It is a technique used by banks, intelligence agencies and high-profile institutions to validate the identity of an individual by comparing signatures and checking for authenticity. In this paper, the approach for the verification of signatures is based on Conventional Neural Network (CNN). This method saves time and energy and also helps to prevent human error during the signature process and lowers chances of fraud in the process of authentication. We achieved test accuracy of 89% and validation accuracy of 93%.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-10-30

Issue

Volume 3, Issue 7, September-October-2018

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Utkarsh Shukla, Srishti Verma, Tushar Gwal, Atul Kumar Verma, " Signature Verification Using CNN with Information Retrieval, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 7, pp.314-319, September-October-2018.