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All Journal Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
Adi Nurhadiyatna
Faculty of Electrical Engineering and Computing, University of Zagreb Zagreb, Croatia
Computer Science & IT

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Offline Signature Identification Using Deep Learning and Euclidean Distance Made Prastha Nugraha; Adi Nurhadiyatna; Dewa Made Sri Arsa
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol 12 No 2 (2021): Vol. 12, No. 02 August 2021
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2021.v12.i02.p04

Abstract

Hand signature is one of human characteristic that human have since birth, which can be used as identity recognition. A high accuracy signature recognition is needed to identify the right owner of signature. This study present signature identification using a combination method between Deep Learning and Euclidean Distance. 3 different signature datasets are used in this study which consist of SigComp2009, SigComp2011, and private dataset. Signature images preprocessed using binary image conversion, Region of Interest, and thinning. Several testing scenarios is applied to measure proposed method robustness, such as usage of various Pretrained Deep Learning, dataset augmentation, and dataset split ratio modifier. The best accuracy achieved is 99.44% with high precision rate.
Co-Authors Arsa, Dewa Made Sri Made Prastha Nugraha