Deteksi Serangan Spoofing Pada Citra Wajah menggunakan Ekstraksi Ciri Local Derivative Pattern
DOI:
https://doi.org/10.21108/INDOJC.2018.3.1.213Abstract
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.Downloads
References
Q.-T. P. a. D.-T. D.-N. a. G. B. a. F. G. B. D. Natale, “Face Spoofing Detection Using LDP-TOP,†Image Processing (ICIP), 2016, pp. 404-408, 2016.
J. M. a. A. H. a. M. Pietikainen, “Face Spoofing Detection From Single Images Using Micro-Texture Analysis,†Biometrics, International Joint Conference on, vol. 00, pp. 1-7, 2011.
H. L. a. S. W. a. A. C.Kot, “Face Spoofing Detection With Image Quality Regression,†dalam Image Processing Theory Tools and Applications (IPTA), IEEE, 2016.
G. P. a. L. S. a. Z. Wu, “Eyeblink-based Anti-Spoofing in Face Recognition from a Generic Webcamera,†2007.
K. K. a. H. F. a. M. I. F. a. J. Bigun, “Real-Time Face Detection and Motion Analysis With Application in "Liveness" Assessment,†IEEE Transactions on Information Forensics and Security - Part 2, vol. 2, pp. 548-558, 2007.
W. B. a. H. L. a. N. L. a. W. Jiang, “A Liveness Detection Method For Face Recognition Based on Optical Flow Field,†Image Analysis and Signal Processing, pp. 233-236, 2009.
Z. B. a. J. K. a. A. Hadid, “Face Spoofing Detection Using Color Texture Analysis,†IEEE Transactions on Information Forensics and Security, vol. 11, pp. 1818-1830, 2016.
B. Z. a. Y. G. a. S. M. a. S. Z. a. J. L. a. S. Member, “Local Derivative Pattern Versus Local Binary Pattern: Face Recognition with Higher-Order Local Pattern Descriptor,†IEEE Trans. Image Process, pp. 533-544, 2010.
H. R. a. J. S. a. Y. H. a. X. Y. a. Y. Liu, “Uniform Local Derivative Patterns and Their Application in Face Recognition,†Journal of Signal Processing Systems, vol. 74, pp. 405-416, 2014.
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