FACE AUTHENTICATION USING LOGIC FUSION OF COLOR WITH EFM FEATURE EXTRACTION
Résumé
In this paper, we investigate the use of colour information to face authentication systems. In order to improve the performance
of these systems many colour components have been used. The results in different colorimetric components are combined by
using a logic fusion for classification with different operators. For the extraction of feature vectors we have applied the
Enhanced Fisher linear discriminant Model (EFM) which is presented as an alternative features extraction algorithm to
Principal Component Analysis (PCA) which is widely used in automatic face recognition. We calculate the error rates in the
two sets of data validation and data test according to the Lausane protocol (XM2VTS). The results obtained show that the use
of colour improves the performance of authentication by (3%) compared to greyscale system. This system can be employed in
high security.
Références
Face authentication using logic fusion of Color with EFM Feature Extraction
75
[17] Meriem Fedias, L’apport de la couleur à la
verification d’identité à l’aide des images de visages.
Mémoire de Magistère, Université de Biskra,
Algérie.2007.
[18] A. Gasteratos, M. Vincze, and J.K. Tsotsos
(Eds.):Face Recognition Using a Color PCA
Framework ICVS 2008, LNCS 5008, pp. 373–382,
2008.Springer-Verlag Berlin Heidelberg 2008.
[19] Zhiming Liu; Jian Yang; Chengjun Liu; Extracting
Multiple Features in the CID Color Space for Face
Recognition, image processing IEEE volume 19 issue
9. Sept. 2010.
[20] Jian Yang, Chengjun Liu, Lei Zhang, Color space
normalization: Enhancing the discriminating power of
color spaces for face recognition, Pattern Recognition,
Volume 43, Issue 4, April 2010.
[21] M. Fedias, D. Saigaa “Non linear fusion of colors to
face authentication using EFM method”, Journal of
Applied Computer Science & Mathematics (JACSM),
n°9 (4) Nov 2010, pp. 42-50, Romania.
[22] M. Fedias, D. Saigaa “Non linear fusion of colors to
face authentication using EFM method”, the
International Workshop on Systems Communication
and Engineering in Computer Science CECS’ 2010, 3
to 5 Oct 2010 Batna Algeria (Collaboration with TU-
Berlin German University and University of Batna, to
appear in Springer).
[23] D. Saigaa, M. Fedias, A.Harrag, A.Bouchelaghem,
D.Drif “Color space MS based feature extraction
method for face verification”, the 11th International
conference on hybrid intelligent systems HIS’ 2011, 5
to 8 Dec 2011 Melaka, Malaysia. (IEEE proceeding).
[26] Michal Wozniak, Manuel Graña, Emilio Corchado: A survey
of multiple classifier systems as hybrid systems. Information
Fusion 16: 3-17 (2014)
[27] Hybrid neural intelligent system to predict business failure in
small-to-medium-size enterprisesML BORRAJO, B Baruque,
E Corchado, J Bajo, JM Corchado. International journal of
neural systems 21 (04), 277-296.
[28] M. Fedias, M.S Mimoune, M. Boumehraz, D.Saigaa “Fusion
non linéaire d’espace couleurs à l’authentification de visage à
l’aide d’une Nouvelle méthode MS”, Annals. Computer
Science Series Tome 12, Fasc.1, (Accepted and to appear in
June 2014) , Romania. [1] Turk M. A. et Pentland A. P.: Face recognition using
eigenfaces. IEEE Comput. ScoPress, p. 586-591, June
1991.
[2] Matthew Turk et Alex Pentland: Eigenfaces for
recognition. Journal of cognitive neurosci-ence,
3(1):71–86, 1991.
[3] Wend S. Yambor, Analysis of PCA-based and fisher
discriminantbased image recognition algorithms,
Technical Report CS-00-103, july 2000.
[4] P. Belhumeur, J.P. Hespanha, D.J. Kriegman ,
Eigenfaces vs. Fisherfaces: recognition using class
specific linear projection. IEEE Trans. on Pattern
Analysis and Machine Intelligence, 1997, pp. 711-
720.
[5] M. Fedias, D. Saigaa : L'apport de la couleur à
l'authentification de visage, Conférence in-ternationale
JIG'2007 à Constantine,Algerie, pp. 120-126.
[6] Chengjun Liu and Harry Wechsler “Gabor Feature
Based Classification Using the En-hanced Fisher
Linear Discriminant Model for Face Recognition”,
IEEE Trans. Image Processing, vol. 11, no. 4, pp. 467-
476, 2002.
[7] D. L. Swets and J. Weng, “Using discriminant
eigenfeatures for image retrieval,” IEEE Trans.
Pattern Analysis and Machine Intelligence, vol. 18,
no. 8, pp. 831– 836, 1996.
[8] C. Liu and H.Wechsler, “Robust coding schemes for
indexing and retrieval from large face databases,”
IEEE Trans. on Image Processing, vol. 9, no. 1, pp.
132–137, 2000.
[9] K. Messer, J. Matas, J. Kittler et K. Jonsson :
Xm2vtsdb : The extended m2vts database. Audio- and
Video-based Biometric Person Authentication
(AVBPA), pages 72–77, Mars 1999.
[10] J. Luettin and G. Maitre. “Evaluation protocol for the
extended M2VTS database”. IDIAP, available at:
http://www.ee.surrey.ac.uk/Research
/VSSP/xm2vtsdb/face- a-vbpa2001/protocol.ps, 1998.
[11] K. Etemad and R. Chellappa, “Discriminant analysis
for recognition of human face im-ages,”J. Opt. Soc.
Am. A, vol. 14, pp. 1724– 1733, 1997.
[12] Alain Tremeau, « Représentation numérique des
images couleur », Ecole de Printemps – Images
Couleur, Pau, France, Mars 2001.
[13] Yip, A. & Sinha, P. (2001). Role of Color in Face
Recognition, MIT AI Memos, AIM-2001-035, (Dec
2001).
[14] Marcel, S. & Bengio, S. (2002). Improving Face
Verification Using Skin Color
Information,Proceedings of the International
Conference on Pattern Recognition, pp 378-381,
August 2002.
[15] Rajapakse, M.; Tan, J. & Rajapakse, J. (2004). Color
Channel Encoding with NMF for Face Recognition,
Proceedings of the International Conference on Image
Processing, pp 2007-2010, October 2004.
[16] Youssef, K. & Woo, P.-Y. (2007). A New Method for
Face Recognition Based on Color Information and a
Neural Network, Proceedings of the International
Conference on Natural Computation, pp. 585-589,
9780769528755, China, Aug 2007, IEEE, Haikou.
75
[17] Meriem Fedias, L’apport de la couleur à la
verification d’identité à l’aide des images de visages.
Mémoire de Magistère, Université de Biskra,
Algérie.2007.
[18] A. Gasteratos, M. Vincze, and J.K. Tsotsos
(Eds.):Face Recognition Using a Color PCA
Framework ICVS 2008, LNCS 5008, pp. 373–382,
2008.Springer-Verlag Berlin Heidelberg 2008.
[19] Zhiming Liu; Jian Yang; Chengjun Liu; Extracting
Multiple Features in the CID Color Space for Face
Recognition, image processing IEEE volume 19 issue
9. Sept. 2010.
[20] Jian Yang, Chengjun Liu, Lei Zhang, Color space
normalization: Enhancing the discriminating power of
color spaces for face recognition, Pattern Recognition,
Volume 43, Issue 4, April 2010.
[21] M. Fedias, D. Saigaa “Non linear fusion of colors to
face authentication using EFM method”, Journal of
Applied Computer Science & Mathematics (JACSM),
n°9 (4) Nov 2010, pp. 42-50, Romania.
[22] M. Fedias, D. Saigaa “Non linear fusion of colors to
face authentication using EFM method”, the
International Workshop on Systems Communication
and Engineering in Computer Science CECS’ 2010, 3
to 5 Oct 2010 Batna Algeria (Collaboration with TU-
Berlin German University and University of Batna, to
appear in Springer).
[23] D. Saigaa, M. Fedias, A.Harrag, A.Bouchelaghem,
D.Drif “Color space MS based feature extraction
method for face verification”, the 11th International
conference on hybrid intelligent systems HIS’ 2011, 5
to 8 Dec 2011 Melaka, Malaysia. (IEEE proceeding).
[26] Michal Wozniak, Manuel Graña, Emilio Corchado: A survey
of multiple classifier systems as hybrid systems. Information
Fusion 16: 3-17 (2014)
[27] Hybrid neural intelligent system to predict business failure in
small-to-medium-size enterprisesML BORRAJO, B Baruque,
E Corchado, J Bajo, JM Corchado. International journal of
neural systems 21 (04), 277-296.
[28] M. Fedias, M.S Mimoune, M. Boumehraz, D.Saigaa “Fusion
non linéaire d’espace couleurs à l’authentification de visage à
l’aide d’une Nouvelle méthode MS”, Annals. Computer
Science Series Tome 12, Fasc.1, (Accepted and to appear in
June 2014) , Romania. [1] Turk M. A. et Pentland A. P.: Face recognition using
eigenfaces. IEEE Comput. ScoPress, p. 586-591, June
1991.
[2] Matthew Turk et Alex Pentland: Eigenfaces for
recognition. Journal of cognitive neurosci-ence,
3(1):71–86, 1991.
[3] Wend S. Yambor, Analysis of PCA-based and fisher
discriminantbased image recognition algorithms,
Technical Report CS-00-103, july 2000.
[4] P. Belhumeur, J.P. Hespanha, D.J. Kriegman ,
Eigenfaces vs. Fisherfaces: recognition using class
specific linear projection. IEEE Trans. on Pattern
Analysis and Machine Intelligence, 1997, pp. 711-
720.
[5] M. Fedias, D. Saigaa : L'apport de la couleur à
l'authentification de visage, Conférence in-ternationale
JIG'2007 à Constantine,Algerie, pp. 120-126.
[6] Chengjun Liu and Harry Wechsler “Gabor Feature
Based Classification Using the En-hanced Fisher
Linear Discriminant Model for Face Recognition”,
IEEE Trans. Image Processing, vol. 11, no. 4, pp. 467-
476, 2002.
[7] D. L. Swets and J. Weng, “Using discriminant
eigenfeatures for image retrieval,” IEEE Trans.
Pattern Analysis and Machine Intelligence, vol. 18,
no. 8, pp. 831– 836, 1996.
[8] C. Liu and H.Wechsler, “Robust coding schemes for
indexing and retrieval from large face databases,”
IEEE Trans. on Image Processing, vol. 9, no. 1, pp.
132–137, 2000.
[9] K. Messer, J. Matas, J. Kittler et K. Jonsson :
Xm2vtsdb : The extended m2vts database. Audio- and
Video-based Biometric Person Authentication
(AVBPA), pages 72–77, Mars 1999.
[10] J. Luettin and G. Maitre. “Evaluation protocol for the
extended M2VTS database”. IDIAP, available at:
http://www.ee.surrey.ac.uk/Research
/VSSP/xm2vtsdb/face- a-vbpa2001/protocol.ps, 1998.
[11] K. Etemad and R. Chellappa, “Discriminant analysis
for recognition of human face im-ages,”J. Opt. Soc.
Am. A, vol. 14, pp. 1724– 1733, 1997.
[12] Alain Tremeau, « Représentation numérique des
images couleur », Ecole de Printemps – Images
Couleur, Pau, France, Mars 2001.
[13] Yip, A. & Sinha, P. (2001). Role of Color in Face
Recognition, MIT AI Memos, AIM-2001-035, (Dec
2001).
[14] Marcel, S. & Bengio, S. (2002). Improving Face
Verification Using Skin Color
Information,Proceedings of the International
Conference on Pattern Recognition, pp 378-381,
August 2002.
[15] Rajapakse, M.; Tan, J. & Rajapakse, J. (2004). Color
Channel Encoding with NMF for Face Recognition,
Proceedings of the International Conference on Image
Processing, pp 2007-2010, October 2004.
[16] Youssef, K. & Woo, P.-Y. (2007). A New Method for
Face Recognition Based on Color Information and a
Neural Network, Proceedings of the International
Conference on Natural Computation, pp. 585-589,
9780769528755, China, Aug 2007, IEEE, Haikou.
Comment citer
FEDIAS, M.; S. MIMOUNE, M.; BOUMEHREZ, M..
FACE AUTHENTICATION USING LOGIC FUSION OF COLOR WITH EFM FEATURE EXTRACTION.
Courrier du Savoir, [S.l.], v. 18, juin 2014.
ISSN 1112-3338.
Disponible à l'adresse : >https://revues.univ-biskra.dz./index.php/cds/article/view/651>. Date de consultation : 14 nov. 2024
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