Deteksi Spoofing Wajah Manusia Berbasis Video menggunakan Metode Local Derivative Pattern-Three Orthogonal Planes

  • Febryanti Sthevanie Telkom University
  • Diah Ajeng Dwi Yuniasih Telkom University
  • Kurniawan Nur Ramadhani Telkom University
https://doi.org/10.34818/INDOJC.2020.5.1.376
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Abstract

Saat ini banyak sistem yang menggunakan pengenalan wajah sebagai keamanan. Namun, penggunaan wajah tersebut masih memiliki kerentanan terhadap serangan spoofing, yaitu serangan dengan cara memalsukan foto atau video dari pengguna asli sistem tersebut. Untuk menghindari adanya tindakan kriminal tersebut, diusulkan sebuah sistem yang dapat mendeteksi serangan spoofing menggunakan metode Local Derivative Pattern dari Three Orthogonal Planes. Dataset yang digunakan adalah bersumber dari empat dataset publik yang berbeda yaitu Idiap Replay-Attack Database, MSU MFSD Database, Casia FASD Database dan NUAA Imposter Database yang berformat video. Dari hasil pengujian, pada skenario intra-dataset didapatkan performansi terbaik dengan rata-rata F1-Score 97.77% dan rata-rata HTER 8.47%, sedangkan pada skenario cross-dataset rata-rata F1-Score 74.77% dan rata-rata HTER 29.05%.

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References

S. Z. J. L. Baochang Zhang, Yongsheng Gao. Local derivative pattern versus local binary pattern: Face recognition with high-order local pattern decriptor. 2010.

D. S. Chouhan. Svm kernel functions for classification. 2013.

B. M. D. B. E. R. Dr U S B Raju, A Sridhar Kumar. Texture classification with high order local pattern descriptor: Local derivative pattern. 2010.

GeeksforGeeks. Confusion Matrix in Machine Learning. https://www.geeksforgeeks.org/confusion-matrix-machine-learning/. [Online; accessed 14-January-2019].

A. Jain, Anil K.; Ross. Handbook of Biometrics. Springer, 2008.

M. P. Jukka Maatta, Abdenour Hadid. Face spoofing detection from single images using micro-texture analysis. 2011.

MathWorks. rgb2gray. https://www.mathworks.com/help/matlab/ref/rgb2gray.html, 2018. [Online; accessed 14-January-2019].

G. B. F. G. D. N. Quoc-Tin Phan, Duc-Tien Dang-Nguyen. Face spoofing detection using ldp-top. 2016.

M. Z.-X. Z. R. W. Shichao Zhang, Xuelong Li. Efficient knn classification with different numbers of nearest neighbors. 2018.

E. S. V. N. O. D. W. Sutoyo, T.; Mulyanto. Teori Pengolahan Citra Digital. Penerbit Andi, 2009.

G. Z. Xiaopeng Hong, Yingyue Xu. Lbp-top: a tensor unfolding revisit. 2017.

A. H. Zinelabidine Boulkenafet, Jukka Komulainen. Face spoofing detection using colour texture analysis. 2016.

Published
2020-04-14
How to Cite
Sthevanie, F., Yuniasih, D. A. D., & Ramadhani, K. N. (2020). Deteksi Spoofing Wajah Manusia Berbasis Video menggunakan Metode Local Derivative Pattern-Three Orthogonal Planes. Indonesia Journal on Computing (Indo-JC), 5(1), 53-62. https://doi.org/10.34818/INDOJC.2020.5.1.376
Issue
Vol. 5 No. 1 (2020): Maret, 2020
Section
Computer Science

Copyright (c) 2020 Febryanti Sthevanie, Diah Ajeng Dwi Yuniasih, Kurniawan Nur Ramadhani

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