Commenced in January 2007
Paper Count: 30178
Palmprint Recognition by Wavelet Transform with Competitive Index and PCA
Abstract:This manuscript presents, palmprint recognition by combining different texture extraction approaches with high accuracy. The Region of Interest (ROI) is decomposed into different frequencytime sub-bands by wavelet transform up-to two levels and only the approximate image of two levels is selected, which is known as Approximate Image ROI (AIROI). This AIROI has information of principal lines of the palm. The Competitive Index is used as the features of the palmprint, in which six Gabor filters of different orientations convolve with the palmprint image to extract the orientation information from the image. The winner-take-all strategy is used to select dominant orientation for each pixel, which is known as Competitive Index. Further, PCA is applied to select highly uncorrelated Competitive Index features, to reduce the dimensions of the feature vector, and to project the features on Eigen space. The similarity of two palmprints is measured by the Euclidean distance metrics. The algorithm is tested on Hong Kong PolyU palmprint database. Different AIROI of different wavelet filter families are also tested with the Competitive Index and PCA. AIROI of db7 wavelet filter achievs Equal Error Rate (EER) of 0.0152% and Genuine Acceptance Rate (GAR) of 99.67% on the palm database of Hong Kong PolyU.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1060777Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1387
 D. Zhang and M. Kamel , Survey of Palmprint Recognition, Pattern Recognition Vol. 42, pp. 1408 - 1418, (2009).
 W. K.Kong, D. Zhang and W. Li , Palmprint Feature Extraction using 2-D Filters, Pattern Recognition, Vol. 36, pp. 2339 - 2347, (2003).
 A. Kong and D. Zhang, Orientation Selection Using Modified FCM for Competitive Code-based Palmprint, Pattern Recognition, Vol. 42, pp. 2841-2849, (2009).
 D. Tamrakar and P. Khanna, Analysis of Palmprint Verification Using Wavelet Filter and Competitive Code, IEEE, International conference on Computational Intelligence and Communication Networks (CICN), pp. 20 - 25, (2010).
 D. Tamrakar and P. Khanna, Palmprint verification using competitive index with PCA , IEEE, International conference on Signal Processing, Communication, Computing and Networking Technologies (ICSCCN), pp. 768 - 771, (2011).
 W. Zuo, Z. Lin, Z. Guo and D. Zhang , The Multiscale Competitive Code via Sparse Representation for Palmprint Verification, IEEE, International conference on Computer Vision and Pattern Recognition (CVPR), pp. 2265 - 2272 , (2010).
 D. Zhang, W. K. Kong, J. You and M. Wong, Online Palmprint Identification, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 25(9), pp. 1041-1050, (2003).
 A. Kong, D. Zhang and M. Kamel, Palmprint Identification using Featurelevel Fusion, Pattern Recognition, Vol. 39, pp. 478-487, (2006).
 X.Q. Wu, K.Q. Wang and D. Zhang, Palmprint texture analysis using derivative of Gaussian filters, Proceedings of IEEE International Conferenceon Computational Intelligence and Security, (2006).
 M. K. Goh, T. Connie, A. B. Teoh and D. C. Ngo, A Fast Palm Print Verification System, Proceedings of the International Conference on Computer Graphics, Imaging and Visualization (CGIV-06), (2003).
 W. Jia, D.S. Huang and Zhang D., Palmprint Verification based on Robust Line Orientation Code, Pattern Recognition Vol. 41, pp. 1504- 1513, (2008).
 K. Y. E. Wong, G. Sainarayanan and Chekima A., Palmprint Identification Using Wavelet Energy, International Conference on Intelligent and Advanced Systems, (2007).
 X. Zhou, Y. Peng and M. Yang, Palmprint Recognition Using Wavelet and Support Vector Machines, PRICAI, LNAI 4099, pp. 385-393, (2006).
 Z. Guo, D. Zhang, L. Zhang and W. Zuo , Palmprint verification using binary orientation co-occurrence vector, Pattern Recognition Letters, Vol. 30, pp. 219 - 227, (2009).
 T. Connie, T. Andrew and K. Goh, An Automated Palmprint Recognition System, Image and Vision Computing, Vol. 23, pp. 501-505, (2005).
 M. A. You, and s. Jifeng, Palmprint Recognition Based on 2DPCA Moment Invariant, Fifth International Conference on Image and Graphics, (2009).
 G. Lu, D. Zhang, K. Wang, Palmprint Recognition Using Eigenpalms Features, Pattern Recognition Letters, Vol. 24, pp. 1463-1467, (2003).
 L. M. Borja and O. Fuentes, Object Detection using Image Reconstruction with PCA , Image and Vision Computing, Vol. 27, pp. 2-9, (2009).
 X. Wu, D. Zhang, K. Wang , Fisherpalm Based Palmprint Recognition, Pattern Recognition Letters, Vol. 24 , pp. 2829-2838, (2003).
 D. Hu, G. Feng, and Z. Zhou, Two-dimensional Locality Preserving Projections (2DLPP) with its Application to Palmprint Recognition, Pattern Recognition, Vol. 40, pp. 339-342, (2007).
 D. Pertrovska, G. Chollet and Dorizz B., Guide to Biometric Reference Systems and Performance Evaluation, Springer, (2009).
 D. Zhang, poly-U Palmprint Database, Biometric Research Centre, Hong Kong Polytechnic University, (Online) Available from: (http://www.comp.polyu.edu.hk/╦£biometrics/).