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Face Recognition Using Eigen face Coefficients and Principal Component Analysis

Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Samriti Jindal, Inderpreet Kaur, Shilpi Kumari


Face Recognition is a field of multidimensional applications. A lot of work has been done, extensively on the most of details related to face recognition. This idea of face recognition using PCA is one of them. In this paper the PCA features for Feature extraction are used and matching is done for the face under consideration with the test image using Eigen face coefficients. The crux of the work lies in optimizing Euclidean distance and paving the way to test the same algorithm using Matlab which is an efficient tool having powerful user interface along with simplicity in representing complex images.

Keywords: Matching, PCA, multidimensional, Eigen Face

Digital Object Identifier (DOI):

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[1] Wendy S. Yambor Bruce A. Draper J. Ross Beveridge, "Analyzing PCA based Face Recognition Algorithms: Eigenvector Selection and Distance Measures", July 1, 2000. Available at:
[2] Peter Belhumeur, J. Hespanha, David Kriegman, "Eigenfaces vs. fisherfaces: Recognition using class specific linear projection", IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(7):771 - 720, 1997.
[3] L. Breiman. Bagging predictors. Technical Report Technical Report Number 421, Dept. of Statistics, University of California, Berkeley, 1994.
[4] D. Swets and J. Weng, "Hierarchical discriminant analysis for image retrieval", IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(5):386-401, 1999.
[5] Wendy S. Yambor, "Analysis of PCA Based and Fisher Discriminant- Based Image Recognition Algorithms", M.S. Thesis, July 2000 (Technical Report CS-00-103, Computer Science).
[6] Kyungnam Kim, "Face Recognition using Principle Component Analysis",. International Conference on Computer Vision and Pattern Recognition, pp. 586-591, 1996.
[10] James R. Parker, J R Parker , "Algorithms for Image Processing and Computer Vision", John Wiley & Sons, 1996.
[11] Sankar K. Pal, Ashish Ghosh, Malay K. Kundu, "Soft Computing for Image Processing", Studies in Fuzziness and Soft Computing, Vol. 42, 2000.
[12] Rafael C. Gonzalez, Richard E. Woods, "Digital Image Processing", Pearson Publications, 2000.
[13] Image Processing Handbook by John C. Russ
[14] Handbook of Pattern Recognition and Image Processing by K.S. Fu and T.Y. Young
[15] Li Ma , Tieniu Tan , Yunhong Wang , Dexin Zhang " Personal Identification Based on Iris Texture Analysis" , IEEE Transactions on Pattern Analysis and Machine Intelligence , Vol. 25 No. 12, December 2003.
[16] John Carter, Mark Nixon, "An Integrated Biometric Database", available at:
[17] Arun Rose, Anil Jain and Sharat Pankanti, "A Prototype Hand Geometry Based Verification System", 2nd International Conference on Audio and Video Based Person Authentication, Washington D. C., pp. 166-171, 1999.
[18] Boreki, Guilherm, Zimmer, Alessandro, "Hand Geometry Feature Extraction through Curvature Profile Analysis", XVIII Brazilian Symposium on Computer Graphics and Image Processing, SIBGRAPI, Brazil, 2005.