Face Recognition Based on Gabor Features

Research output: A Conference proceeding or a Chapter in BookConference contribution

1 Citation (Scopus)
3 Downloads (Pure)

Abstract

The paper presents a novel approach for solving face recognition problem. We combine Gabor filters and Principal Component Analysis (PCA) to extract feature vectors; then we apply Support Vector Machine (SVM), the most powerful discriminative method, and AdaBoost, a meta-algorithm, for classification. Experiments for the proposed method have been conducted on two public face database AT&T and FERET. The results show that the proposed method could improve the classification rates
Original languageEnglish
Title of host publicationVisual Information Processing EUVIP 2011, 3rd European Workshop
EditorsAzeddine Beghdadi, Abdesselam Bouzerdoum, Giuseppe Boccignone, Mohamed-Chaker Larabi
Place of PublicationParis
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages264-269
Number of pages6
Volume1
ISBN (Print)9781457700729
DOIs
Publication statusPublished - 2011
EventEuropean Workshop on Visual Information Processing - Paris, Paris, France
Duration: 4 Jul 20116 Jul 2011

Conference

ConferenceEuropean Workshop on Visual Information Processing
CountryFrance
CityParis
Period4/07/116/07/11

Fingerprint

Face recognition
Gabor filters
Adaptive boosting
Principal component analysis
Support vector machines
Experiments

Cite this

Tran, D., Huang, X., & Chetty, G. (2011). Face Recognition Based on Gabor Features. In A. Beghdadi, A. Bouzerdoum, G. Boccignone, & M-C. Larabi (Eds.), Visual Information Processing EUVIP 2011, 3rd European Workshop (Vol. 1, pp. 264-269). Paris: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EuVIP.2011.6045542
Tran, Dat ; Huang, Xu ; Chetty, Girija. / Face Recognition Based on Gabor Features. Visual Information Processing EUVIP 2011, 3rd European Workshop. editor / Azeddine Beghdadi ; Abdesselam Bouzerdoum ; Giuseppe Boccignone ; Mohamed-Chaker Larabi. Vol. 1 Paris : IEEE, Institute of Electrical and Electronics Engineers, 2011. pp. 264-269
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title = "Face Recognition Based on Gabor Features",
abstract = "The paper presents a novel approach for solving face recognition problem. We combine Gabor filters and Principal Component Analysis (PCA) to extract feature vectors; then we apply Support Vector Machine (SVM), the most powerful discriminative method, and AdaBoost, a meta-algorithm, for classification. Experiments for the proposed method have been conducted on two public face database AT&T and FERET. The results show that the proposed method could improve the classification rates",
keywords = "Face Recognition, Gabor Feature",
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Tran, D, Huang, X & Chetty, G 2011, Face Recognition Based on Gabor Features. in A Beghdadi, A Bouzerdoum, G Boccignone & M-C Larabi (eds), Visual Information Processing EUVIP 2011, 3rd European Workshop. vol. 1, IEEE, Institute of Electrical and Electronics Engineers, Paris, pp. 264-269, European Workshop on Visual Information Processing, Paris, France, 4/07/11. https://doi.org/10.1109/EuVIP.2011.6045542

Face Recognition Based on Gabor Features. / Tran, Dat; Huang, Xu; Chetty, Girija.

Visual Information Processing EUVIP 2011, 3rd European Workshop. ed. / Azeddine Beghdadi; Abdesselam Bouzerdoum; Giuseppe Boccignone; Mohamed-Chaker Larabi. Vol. 1 Paris : IEEE, Institute of Electrical and Electronics Engineers, 2011. p. 264-269.

Research output: A Conference proceeding or a Chapter in BookConference contribution

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T1 - Face Recognition Based on Gabor Features

AU - Tran, Dat

AU - Huang, Xu

AU - Chetty, Girija

PY - 2011

Y1 - 2011

N2 - The paper presents a novel approach for solving face recognition problem. We combine Gabor filters and Principal Component Analysis (PCA) to extract feature vectors; then we apply Support Vector Machine (SVM), the most powerful discriminative method, and AdaBoost, a meta-algorithm, for classification. Experiments for the proposed method have been conducted on two public face database AT&T and FERET. The results show that the proposed method could improve the classification rates

AB - The paper presents a novel approach for solving face recognition problem. We combine Gabor filters and Principal Component Analysis (PCA) to extract feature vectors; then we apply Support Vector Machine (SVM), the most powerful discriminative method, and AdaBoost, a meta-algorithm, for classification. Experiments for the proposed method have been conducted on two public face database AT&T and FERET. The results show that the proposed method could improve the classification rates

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DO - 10.1109/EuVIP.2011.6045542

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BT - Visual Information Processing EUVIP 2011, 3rd European Workshop

A2 - Beghdadi, Azeddine

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Tran D, Huang X, Chetty G. Face Recognition Based on Gabor Features. In Beghdadi A, Bouzerdoum A, Boccignone G, Larabi M-C, editors, Visual Information Processing EUVIP 2011, 3rd European Workshop. Vol. 1. Paris: IEEE, Institute of Electrical and Electronics Engineers. 2011. p. 264-269 https://doi.org/10.1109/EuVIP.2011.6045542