State of Art Survey Signature Verification Techniques 2019

  • Mitesh Parmar
  • Nupur Puranik
  • Dhruva Joshi
  • Sonal Malpani
  • Bhushan Thakare
Keywords: SRSS, Cognitive Inspired Model, Signature Duplication

Abstract

Currently a lot of time is needed for the verification of signature manually.  The need of developing an automated checking system is felt because of signature forgery in various transactions. The dynamic signature is a biometric trait which is used in identification. The aim of the model is identifying correct signature for reducing fraudulent transactions. The idea is to duplicate a given signature a number of times and train the verifier with each of the resulting signatures. Automatic signature verification is an application of image processing. Signature Verification can be 1) Online (Dynamic) 2) Offline (Static). For duplication of signature one approach is using the Cognitive Inspired Model. The approach for creating human like signatures can be done by introducing Intra-Component and Inter-Component variability. This system, with a single reference signature, is capable of achieving a similar performance to standard verifiers trained with up to five signature specimens. For classification classifiers like SVM, CNN can be used.

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Published
2020-03-26
How to Cite
Parmar, M., Puranik, N., Joshi, D., Malpani, S., & Thakare, B. (2020). State of Art Survey Signature Verification Techniques 2019. Asian Journal For Convergence In Technology (AJCT), 5(3), 91-96. Retrieved from http://www.asianssr.org/index.php/ajct/article/view/927