Manuscript Title:

HAND WRITTEN SIGNATURE RECOGNITION USING DEEP LEARNING NETWORKS

Author:

ASHOK KUMAR YADAV, T. SRINIVASULU

DOI Number:

DOI:10.17605/OSF.IO/9TSY3

Published : 2022-03-10

About the author(s)

1. ASHOK KUMAR YADAV - ECE, JNTU, Hyderabad.
2. T. SRINIVASULU - UCE, Kakatiya University, Warangal.

Full Text : PDF

Abstract

Hand Written Signature Recognition is an indispensable biometric method for plan to see whether or not accessible mark is truly phony or genuine. It’s obligatory in forestalling adulteration of reports in checking the lawfulness of archives like drafts, identification, visa and modern financial transactions. Our examination point is to automatize the technique for written by hand Signature recognition by applying Convolutional Neural Network. Proposed model depends on VGG16 plan, and that we utilized our own dataset to prepare our model with move learning. Once characterizing whether or not a given mark was falsification or genuine, we will quite often arrive at the exactness of almost 100% with utilization of my restrictive dataset. We tend to also performed many investigations changing the classes of preparing information and forecast undertaking to make it extra pertinent to genuine applications, that our procedure seems promising.


Keywords

Hand Written Signature, Convolutional Neural Network, FRR, FAR, Support Vector Machine.