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Andi Maulidinnawati A. K. Parewe
Brawijaya University

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Offline Signature Recognition using Back Propagation Neural Network Asyrofa Rahmi; Vivi Nur Wijayaningrum; Wayan Firdaus Mahmudy; Andi Maulidinnawati A. K. Parewe
Indonesian Journal of Electrical Engineering and Computer Science Vol 4, No 3: December 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v4.i3.pp678-683

Abstract

The signature recognition is a difficult process as it requires several phases. A failure in a phase will significantly reduce the recognition accuracy. Artificial Neural Network (ANN) believed to be used to assist in the recognition or classification of the signature. In this study, the ANN algorithm used is Back Propagation. A mechanism to adaptively adjust the learning rate is developed to improve the system accuracy. The purpose of this study is to conduct the recognition of a number of signatures so that can be known whether the recognition which is done by using the Back Propagation is appropriate or not. The testing results performed by using learning rate of 0.64, the number of iterations is 100, and produces an accuracy value of 63%.
Co-Authors Asyrofa Rahmi Vivi Nur Wijayaningrum Wayan Firdaus Mahmudy