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All Journal Infotekmesin
Ano Rangga Rahardika
Institut Teknologi Sepuluh Nopember
Computer Science & IT Electrical & Electronics Engineering Mechanical Engineering

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An Enhanced Dynamic Signature Verification using the X and Y Histogram Features Aris Tjahyanto; Ano Rangga Rahardika; Ary Mazharuddin Shiddiqi
Infotekmesin Vol 12 No 2 (2021): Infotekmesin: Juli 2021
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v12i2.668

Abstract

Dynamic signature verification by using histogram features is a well-known signature forgery detection technique due to its high performance. However, this technique is often limited to angular histograms derived from vectors containing two adjacent points. We propose additional new features from the X and Y histograms to overcome the limitation.  Our experiments indicate that our technique produced Under Curve Area AUC values 0.80 to detect skilled forgery and 0.91 for random forgery. Our method performed best when the verification system uses 12 of the most dominant features.  This setup produced AUC values of 0.80 to detect skilled forgery and 0.93 for random forgery. These results outperformed the original technique when the X and Y histogram features are not used that produced AUC values of 0.78 to detect skilled forgery and 0.90 for random forgery.
Co-Authors Aris Tjahyanto Ary Mazharuddin Shiddiqi