EKSTRAKSI FITUR HU MOMENT DALAM IDENTIFIKASI KEASLIAN TANDA TANGAN DIGITAL

Yovi Apridiansyah; Ardi Wijaya; aka Rapino; Dedi Abdullah

doi:10.47111/jti.v20i2.25807

Authors

Yovi Apridiansyah Universitas Muhammadiyah Bengkulu
Ardi Wijaya Universitas Muhammadiyah Bengkulu
aka Rapino Universitas Muhammadiyah Bengkulu
Dedi Abdullah Universitas Muhammadiyah Bengkulu

DOI:

https://doi.org/10.47111/jti.v20i2.25807

Keywords:

Digital signature, Hu Moments, feature extraction, forgery detection, image processing

Abstract

Digital signature forgery poses a serious threat in the era of document digitalization, as widely accessible image editing software can be exploited to manipulate signatures with high precision. This study designs and implements a static digital signature authenticity detection system based on Hu Moments feature extraction using MATLAB. The method involves preprocessing stages including image resizing (200×200 pixels), grayscaling, and binarization, followed by the extraction of seven Hu Moment invariant values that are robust against translation, rotation, and scale variations. The dataset consists of 120 signature images collected from 30 subjects (4 samples per person), divided into 90 training data and 30 testing data. System evaluation using a confusion matrix demonstrated excellent performance, achieving a precision of 100%, recall of 93%, and accuracy of 93%. This study proves that Hu Moments are effective as a global shape descriptor for distinguishing genuine and forged signatures, and contributes new insights to the field of digital forensics and electronic document security.

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DOI: 10.47111/jti.v20i2.25807 DOI URL: https://doi.org/10.47111/jti.v20i2.25807

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