An Improved Method for Face Recognition Based on SVM in Frequency Domain

• Autorzy: Amine A. , Ghouzali S. , Rziza M. , Aboutajdine D.
• Języki publikacji: EN

Abstrakty

EN

We examine the problem of discriminating between objects of more than two classes using "minimum information". Discrete Cosine Transforms (DCT) represents a computationally simple and efficient method that preserves the structure of the data without introducing significant distortion. In this paper, an efficient face recognition method combined DCT and Support Vector Machine (SVM) is proposed. The underlying algorithm is derived by applying DCT to several regions of a face image. Only a small subset of the DCT coefficients is retained by truncating high frequency DCT components in each block. Selected DCT features are then subjected to SVM for class separability enhancement before being used for face recognition. This leads to a new, low-dimensional representation of images which allows for a fast and simple classification. In this context, we have performed a large number of experiments using two popular face databases: ORL and Yale, and comparisons using PCA, LDA, ICA, MLP, etc. Experimental results show that the proposed method performs better than traditional approaches in terms of both efficiency and accuracy.

Słowa kluczowe

EN

face recognition; feature extraction; support vector machine (SVM); discrete cosine transform

• Wydawca: Institute of Information Technology of the Warsaw University of Life Sciences – SGGW
• Czasopismo: Machine Graphics and Vision
• Rocznik: 2009
• Tom: Vol. 18, No. 2
• Strony: 187--199
• Opis fizyczny: Bibliogr. 20 poz., il., wykr.

Twórcy

autor

Amine A.

autor

Ghouzali S.

autor

Rziza M.

autor

Aboutajdine D.

• GSCM-LRIT, Faculty of Sciences, Mohammed V-Agdal University, B.P. 1014 Rabat, Morocco

Bibliografia

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