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Signature Recognition Using Backpropagation Neural Network

  • Yucel InanEmail author
  • Boran Sekeroglu
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 896)

Abstract

Imitation or the fake signatures is the global fraud that cause the waste of financial sources, time and human effort. For this reason, signature recognition is the most widely used biometrics system for security and personal identification. Signatures are the most complex human patterns which are used to identify and approve the authorized persons. They can be varied according to the paper and pen influences, and human psychology and characteristics at the signature moment. Therefore, effective recognition of signatures is required in order to minimize the fraud. The usage of neural networks in biometrics, yet signature recognition, provides more steady and accurate identification thus authorization of person. This paper presents the preliminary results of developed offline signature recognition system using backpropagation neural network. Signature database is created by collecting the multiple signatures of 27 persons and the accuracy of the system is tested under artificially created conditions. System achieved 86% of highest recognition rate.

Keywords

Signature recognition Neural networks Backpropagation 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer EngineeringNear East UniversityNicosia, Mersin 10Turkey
  2. 2.Department of Information Systems EngineeringNear East UniversityNicosia, Mersin 10Turkey

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