SIGNATURE VERIFICATION USING NEURAL NETWORKS

SIGNATURE VERIFICATION USING NEURAL NETWORKS

TEAM GUIDE:
Mrs.Jananee J

Head of the Department Biomedical Engineering

TEAM MEMBERS:
BINCY M JACOB [1RG19BM006] MOHAMMED NIHAL [1RG19BM017] RHIYA ELIZABETH ROJI [1RG19BM022] VISHNU [1RG19BM032]

RAJIV GANDHI INSTITUTE OF TECHNOLOGY

(Affiliated to Visvesvaraya Technological University, Belgaum) Cholanagar, R. T. Nagar Post, Bengaluru-560032 DEPARTMENT OF BIOMEDICAL ENGINEERING

ABSTRACT

Signatures are predominantly used to verify an individual's authenticity. In this project we present new improved off-line signature verification system using global and texture features of signatures.The proposed technique in this research will assist individuals in characterizing signatures in order to check whether they are genuine or forged. In this proposed project an algorithm to validate signatures using CNN (Convolution neural network), Siamese neural network and VGG16 (Visual geometry group of transfer learning) models in our system. Authentic and competent forging signatures are used to test the approach. Results obtained by our proposed algorithm are more efficient than most of the existing techniques.