Journal of technical research and development

Articles

Vol. 1 No. 3 (2023):

NEURAL NETWORK APPROACH FOR VERIFICATION OF HANDWRITTEN SIGNATURES IN OFF-LINE MODE

  • Umidjon Akhundjanov
Submitted
November 30, 2023
Published
2023-12-02

Abstract

This paper describes the results of recognizing handwritten signatures using a convolutional neural network. For the experiments, we used a database of handwritten signatures of 40 people, made on paper, as well as publicly available databases of handwritten signatures: BHSig260-Bengali, BHSig260-Hindi, CEDAR. A database of handwritten signatures of 40 people, 10 genuine and 10 fake signatures for each person, made by other people, were collected. For classification, four options were used to reduce the signatures to sizes: 200×120, 250×150, 300×150 and 400×200 pixels.

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