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Warianty tytułu
Języki publikacji
Abstrakty
In this paper, a new similarity measure is developed for human face recognition, namely, weighted matrix distance. The key difference between this metric and the standard distances is the use of matrices and weights rather than the vectors only. The two feature matrices are obtained by two-dimensional principal component analysis (2DPCA). The weights are the inverse of the eigenvalues sorted in decreasing order of the covariance matrix of all training face matrices. Experiments are performed under illumination and facial expression variations using four face image databases: ORL, Yale, PF01 and a subset of FERET. The results demonstrate the effectiveness of the proposed weighted matrix distances in 2DPCA face recognition over the standard matrix distance metrics: Yang, Frobenius and assembled matrix distance (AMD).
Czasopismo
Rocznik
Tom
Strony
207--221
Opis fizyczny
Bibliogr. 11 poz., rys., tab.
Twórcy
autor
autor
- Laboratoire d'Automatique et Informatique, Guelma -LAIG- Université, 8 mai 1945 de Guelma, Algérie, BP.401, Guelma, 24000, Algérie
Bibliografia
- [1] P. N. Belhumeur, J. P. HESPANHA and D. J. KRIEGMAN: Eigenfaces vs Fisher-faces: Recognition using class specific linear projection. IEEE Trans, on Pattern Analysis and Machine Intelligence, 19(7), (1997), 711-720.
- [2] Ch. Rouabhia and H. Tebbikh: Hybrid feature extraction-based approach for partial parts representation and recognition. American Institute ofPhysics Proceed-ings (AlP), Intelligent Systems and Automation, 1019 (2008), 20-24.
- [3] M. A. TURK and A. P. PENTLAND: Eigenfaces for recognition. J. Of Cognitive Neu-wscience, 3(1), (1991), 71-86.
- [4] J. Yang, D. Zhang, A.F. Frangi and J-Y. Yang: Two dimensional PCA: A new approach to appearance-based face representation and recognition. IEEE Trans, on Patiem Analysis and Machinę Intelligence, 26(1), (2004).
- [5] J. YANG and J-Y. YANG: From image vector to matrix: A straightforward image projection technique-IMPCA vs. PCA. Pattern Recognition, 35(9), (2002), 1997-1999.
- [6] Y. Gao and M. K. H. LEUNG: Face recognition using linę edge eap. IEEE Trans. on Pattern Analysis and Machine Intelligence, 24(6), (2002).
- [7] W. Zuo, K. Wang and D. Zhang: Assembled matrix distance metric for 2DPCA-based face and palmprint recognition. Proc. of 4 th Int. Conf. on Machine Learning and Cybernetics, (2005), Guangzhou.
- [8] M. Visani, C. Garcia and J-M. Jolion: Face recognition using modular bi-linear discriminant analysis. Proc. ofthe Int. Conf. on Visual Information Systems, (2005), Amsterdam.
- [9] Z. DAOOJANG and Z. Zhi-Hua: (2D)2PCA: Two-directional two-dimensional PCA for efficient face representation and recognition. Neuwcomputing, 69 (2005), 224-231.
- [10] M. BENGHERABI, L. MEZAI, F. Harizi, M. CHERIET and A. GUESSOUM: Face recognition based on 2DPCA, DIAPCA and DIA2DPCA in DCT domain. The 5th Int. Multi-Conference on Systems, Signals and Devices, IEEE SSD, Amman, Jordan, (2008).
- [11] CH. Rouabhia and H. Tebbikh: Feature matrices fusion and AMD-based tech-nique for face idenlification. 2nd Int. Conf. on Systems and Processing Information (ICSIP’11), Guelma, Algeria, (2011).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSW3-0081-0012