Biometric authenticator algorithm based on multiresolution analysis

Kerrache Soumia, Beladgham Mohammed, Hamza Aymen, Kadri Ibrahim

Abstract


In this paper, we propose a feature extraction method for two-dimensional imageauthentication algorithm using curvelet transform and principal component analysis(PCA). Since wavelet transform can not adequately describe facial curves features,Theproposed approach involves image denoising applying a 2D-Curvelet transform toachieve compact representations of curves singularities. To assess the performanceof the presented method, we have employed three classifification techniques: Neuralnetworks (NN), K-Nearest Neighbor (KNN) and Support Vector machines (SVM).Extensive experimental results and comparison with the existing methods show the effectiveness of the proposed recognition method in the ORL face database and CASIAiris database.

Keywords


Biometric authentication; Classifification algorithmes; Curvelet transform; Feature extraction; Multiresolution analysis

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DOI: http://doi.org/10.11591/ijeecs.v20.i3.pp1332-1341

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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