Open Access Open Access  Restricted Access Subscription or Fee Access

A Comparative Analysis of Human Face Recognition Technique PCA and LDA, KPCA Based on Indian Image Dataset

Rishi Kumar Soni

Abstract


Many statistical techniques for image recognition have been proposed in recent years, different researchers have given the contradictory results when they compared them, In this paper, we compare the two statistical algorithms for image recognition, PCA (Principal Component Analysis), LDA (Linear Discriminant Analysis), linear subspace selection technique and one non linear subspace selection technique KPCA (Kernel Principal Component Analysis) under same conditions. An Indian image data set is used as training and testing data.

Keywords


Face Recognition, PCA, LDA, KPCA, Linear, Non-Linear, Indian Image Data Set, Distance.

Full Text:

PDF

References


K. Baek, B. Draper, J.R. Beveridge, K. She, "PCA vs. ICA: A Comparison on the FERET Data Set", Proc. of the Fourth International Conference on Computer Vision, Pattern Recognition and Image Processing, Durham, NC, USA, 8-14 March 2002, pp. 824-827.

J.R. Beveridge, K. She, B. Draper, G.H. Givens, "A Nonparametric Statistical Comparison of Principal Component and Linear Discriminant Subspaces for Face Recognition", Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, December 2001, Kaui, HI, USA, pp. 535- 542.

A. Martinez, A. Kak, "PCA versus LDA", IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 23, No. 2, February 2001, pp. 228-233.

P. Belhumeur, J. Hespanha, D. Kriegman, "Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection", Proc. of the Fourth European Conference on Computer Vision, Vol. 1, 14-18 April 1996, Cambridge, UK, pp. 45-58.

P. Navarrete, J. Ruiz-del-Solar, "Analysis and Comparison of Eigenspace-Based Face Recognition Approaches", International Journal of Pattern Recognition and Artificial Intelligence, Vol. 16, No. 7, November 2002, pp. 817-830.

M. A. Turk, and A. P. Pentland, “Face recognition using Eigenfaces”, pp. 586-591, IEEE, 1991.

L. Sirovich, and M. Kirby, “Low-dimensional Procedure for the Characterization of Human Faces”, pp. 519-524, Journal of the Optical Society of America, Vol. 4, No. 3, March 1987.

V. Bruce, “Identification of Human Faces”, pp. 615-619, Image Processing and Its Applications, Conference Publication No. 465, IEEE, 1999.

PCA and LDA based Neural Networks for Human Face Recognition Alaa Eleyan and Hasan Demirel Eastern Mediterranean University Northern Cyprus.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.