Deteksi Serangan Spoofing Pada Citra Wajah menggunakan Ekstraksi Ciri Local Derivative Pattern

Authors

  • Ni Gusti Ayu Mirah Eka Darmayanti Universitas Telkom
  • Kurniawan Nur Ramadhani Universitas Telkom
  • Anditya Arifianto Universitas Telkom

DOI:

https://doi.org/10.21108/INDOJC.2018.3.1.213

Abstract

Pada penelitian ini, diusulkan sistem pendeteksi serangan spoofing pada citra wajah manusia menggunakan metode ekstraksi ciri Local Derivative Pattern (LDP). Metode klasifikasi yang digunakan adalah k-Nearest Neighbour (k-NN) dan Support Vector Machine (SVM). Penelitian ini menggunakan NUAA Imposter and Photograph Database sebagai datasetnya. Parameter optimal untuk ekstraksi ciri menggunakan LDP, adalah sebagai berikut: LDP orde ke-2 dengan radius bernilai 5 yang bersifat overlapping non-uniform menggunakan algoritma klasifikasi SVM dengan kernel Radial Basis Function. Performansi terbaik didapatkan menggunakan F1-Score sebesar 99.8%. Pola uniform pada LDP mempercepat waktu komputasi dengan rata-rata 2.09 detik, sedangkan waktu komputasi pola non-uniform yaitu 5.49 detik.

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References

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Published

2018-05-23

How to Cite

Eka Darmayanti, N. G. A. M., Ramadhani, K. N., & Arifianto, A. (2018). Deteksi Serangan Spoofing Pada Citra Wajah menggunakan Ekstraksi Ciri Local Derivative Pattern. Indonesian Journal on Computing (Indo-JC), 3(1), 55–64. https://doi.org/10.21108/INDOJC.2018.3.1.213

Issue

Vol. 3 No. 1 (2018): Maret, 2018

Section

Computer Science

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