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All Journal JSAI (Journal Scientific and Applied Informatics)
Muhammad Hikmal Febrian
Universitas Muhammadiyah Bengkulu
Computer Science & IT

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Penerapan Metode Ekstraksi Fitur Geometris, Hog, dan Hu Moment Pada Citra Tanda Tangan Digital Menggunakan Support Vector Machine (SVM) Muhammad Hikmal Febrian; Erwin Dwika Putra; Ardi Wijaya; Muntahanah
JSAI (Journal Scientific and Applied Informatics) Vol 9 No 2 (2026): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v9i2.10910

Abstract

The increasing use of electronic documents has heightened the need for fast, accurate, and objective digital signature verification systems. This study proposes a digital signature recognition system by combining Geometric Features, Histogram of Oriented Gradients (HOG), and Hu Moment feature extraction with a Support Vector Machine (SVM) classifier using the Radial Basis Function (RBF) kernel. A dataset of 500 signature images from 50 individuals was divided into training, validation, and testing sets using an 80:10:10 ratio. The proposed workflow includes image preprocessing, feature extraction, feature vector construction, model training, and evaluation using a confusion matrix. Experimental results show that the combined feature extraction methods effectively represent both global and local signature characteristics. The proposed model correctly classified 46 of 50 testing samples, achieving 92.00% accuracy, 88.00% precision, 92.00% recall, and an 89.33% F1-score, demonstrating its effectiveness for automatic digital signature recognition and electronic document authentication.
Co-Authors Muntahanah Putra, Erwin Dwika Wijaya, Ardi