Work

Signify: Signature Verification Technique using Convolutional Neural Network

Year: 2019

Type: article

Abstract: Signature is one of the biometric traits that are being used in person authentication and due to its dominant usage; it became one of the top subjects of forgery. In this study, a signature verification using Convolutional Neural Network (CNN) is proposed. With the use of transfer learning, inception-v3 is mainly used for the feature extraction of data samples and for classification of signatures. The proposed method is assessed on dataset of handwritten signatures gathered from 4 people with 100 signatures each. The testing results determine the threshold value which is 96.43%. Factors that affect the accuracy of the result were also identified.

Source: International Journal of Recent Technology and Engineering (IJRTE)

DOI: 10.35940/ijrte.b1015.078219

Authors: Alexandra Mae C. Laylo, Mark Daryl A. Decillo, Louie Andrew F. Boo, Jeffrey S. Sarmiento

Language: English

Topic: Handwritten Text Recognition Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4241501271

FWCI: 0.192

Cites:

Cited by: 3

Related to: 10