Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Novel Approach of Palm-Line Extraction
ICIG '04 Proceedings of the Third International Conference on Image and Graphics
On image matrix based feature extraction algorithms
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Personal Identification Using Palmprint and Contourlet Transform
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Computerized Detection of Pulmonary Nodule Based on Two-Dimensional PCA
ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part II
An evaluation of wavelet kernels for palmprint based recognition
AMDO'10 Proceedings of the 6th international conference on Articulated motion and deformable objects
A feature level multimodal approach for palmprint identification using directional subband energies
Journal of Network and Computer Applications
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Palmprint recognition received many researchers’ attention because of it’s low resolution and cheap devices. As other biometrics, algebraic feature is the prevailing method for palmprint recognition. PCA (principal component analysis) is one prevailing algebraic transformation. It has been a successful feature detection method for pattern recognition. It deals with image vector whose dimension is usually high. 2DPCA is a novel PCA method for image matrix, and it can calculate the covariance matrix more precise. In this paper we apply the new 2DPCA method to palmprint recognition, and we make an improvement in the selection of principal components. In our method we select the principal component that is better for classification. At last we do the improved 2DPCA on the row and column direction to reduce dimension in both direction. Then we apply the method to PolyU Palmprint Database. The experiment result shows that our method got more recognition rate with lower dimensions.