Offline Handwritten Signature Verification using Ne ural Network

Authors

  • Pallavi V. Hatkar Department of Electronics Engineering, TKIET Warana, India
  • Prof.B.T.Salokhe Department of Electronics Engineering, TKIET Warana, India
  • Ashish A.Malgave Department of Electrical Engineering, AMGOI Wathar, India

Keywords:

Neural Networks Approach, Methodology, Result and Discussion

Abstract

The different biometric techniques have been discussed for ident ification. Such as face reading, fingerprint recognition and retina scanning and these are known as vision based i dentification. There are non vision based identifications such as signature verification and the voice recogni tion. Signature verification plays a vital role in the field of the financial, commercial and for the legal matters. Signature by any person considered as the approval for any work so the signature is the preferred authenticat ion. In this paper signature verification is done by means of image processing, geometric feature extraction and by using neural network technique.

Published

2021-03-27

Issue

Vol. 2 No. 1 (2015): IJIERT

Section

Articles

License

Creative Commons License

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

Under the Creative Commons Attribution- 4.0 International License (CC BY-4.0 DEED).

You are free to:

  1. Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
  2. Adapt — remix, transform, and build upon the material for any purpose, even commercially.
  3. The licensor cannot revoke these freedoms as long as you follow the license terms.

Under the following terms:

  1. Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  2. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Notices:

You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.

No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.

How to Cite

Pallavi V. Hatkar, Prof.B.T.Salokhe, & Ashish A.Malgave. (2021). Offline Handwritten Signature Verification using Ne ural Network . International Journal of Innovations in Engineering Research and Technology, 2(1), 1-5. https://repo.ijiert.org/index.php/ijiert/article/view/264