NDLI: Color space MS-based feature extraction method for face verification

Content Provider	IEEE Xplore Digital Library
Author	Saigaa, D. Fedias, M. Harrag, A. Bouchelaghem, A. Drif, M.
Copyright Year	2011
Description	Author affiliation: Department of Electronics, Faculty of Technology, University Mohamed Khider Biskra, BP 145 Biskra 07000 Algeria (Saigaa, D.; Fedias, M.) \|\| Department of Electronics, Faculty of Technology University Mohamed Boudiaf Msila BP 166 Ichbilia 28000 Algeria (Harrag, A.; Bouchelaghem, A.; Drif, M.)
Abstract	In the last years, face verification has gained a great interest in the pattern recognition community and in many application fields. It is among the most attractive research areas because face images can be captured in a non-intrusive way. Many algorithms have been developed in this area, among them the Principal Component Analysis (PCA) is a typical face based technique which considers face as global feature. However, PCA method suffers the disadvantage in terms of discriminant ability and large computational load. Its performance deteriorates especially in the present of varying lighting condition and facial expression. This paper proposes a face authentication method using color information based on a new simple feature extraction technique using face image Mean and Standard deviation (MS) features. The results of evaluation carried out on XM2VTS face database show that MS-based features outperforms PCA-features for all tested color spaces, with best score for the MS-based features using the S component of the HSV (90.44%). In addition, to be stable in different color spaces, MS-based technique proves to be quite stable between validation and tests conditions, which showed strength and robustness of MS-features. The Robustness and ease of extraction make MS-features ideal candidates for a real time application with limited resources.
Starting Page	328
Ending Page	333
File Size	332956
Page Count	6
File Format	PDF
ISBN	9781457721519
e-ISBN	9781457721526
DOI	10.1109/HIS.2011.6122127
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-05
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Image color analysis Databases feature extraction face recognition Feature extraction Vectors Face Principal component analysis pattern recognition
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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