Palmprint Recognition by Wavelet Transform with Competitive Index and PCA
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.
[1] D. Zhang and M. Kamel , Survey of Palmprint Recognition, Pattern
Recognition Vol. 42, pp. 1408 - 1418, (2009).
[2] W. K.Kong, D. Zhang and W. Li , Palmprint Feature Extraction using
2-D Filters, Pattern Recognition, Vol. 36, pp. 2339 - 2347, (2003).
[3] A. Kong and D. Zhang, Orientation Selection Using Modified FCM for
Competitive Code-based Palmprint, Pattern Recognition, Vol. 42, pp.
2841-2849, (2009).
[4] 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).
[5] 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).
[6] 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).
[7] 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).
[8] A. Kong, D. Zhang and M. Kamel, Palmprint Identification using Featurelevel
Fusion, Pattern Recognition, Vol. 39, pp. 478-487, (2006).
[9] 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).
[10] 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).
[11] W. Jia, D.S. Huang and Zhang D., Palmprint Verification based on
Robust Line Orientation Code, Pattern Recognition Vol. 41, pp. 1504-
1513, (2008).
[12] K. Y. E. Wong, G. Sainarayanan and Chekima A., Palmprint Identification
Using Wavelet Energy, International Conference on Intelligent and
Advanced Systems, (2007).
[13] X. Zhou, Y. Peng and M. Yang, Palmprint Recognition Using Wavelet
and Support Vector Machines, PRICAI, LNAI 4099, pp. 385-393, (2006).
[14] 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).
[15] T. Connie, T. Andrew and K. Goh, An Automated Palmprint Recognition
System, Image and Vision Computing, Vol. 23, pp. 501-505, (2005).
[16] M. A. You, and s. Jifeng, Palmprint Recognition Based on 2DPCA Moment
Invariant, Fifth International Conference on Image and Graphics,
(2009).
[17] G. Lu, D. Zhang, K. Wang, Palmprint Recognition Using Eigenpalms
Features, Pattern Recognition Letters, Vol. 24, pp. 1463-1467, (2003).
[18] L. M. Borja and O. Fuentes, Object Detection using Image Reconstruction
with PCA , Image and Vision Computing, Vol. 27, pp. 2-9, (2009).
[19] X. Wu, D. Zhang, K. Wang , Fisherpalm Based Palmprint Recognition,
Pattern Recognition Letters, Vol. 24 , pp. 2829-2838, (2003).
[20] 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).
[21] D. Pertrovska, G. Chollet and Dorizz B., Guide to Biometric Reference
Systems and Performance Evaluation, Springer, (2009).
[22] D. Zhang, poly-U Palmprint Database, Biometric Research Centre,
Hong Kong Polytechnic University, (Online) Available from:
(http://www.comp.polyu.edu.hk/˜biometrics/).
[1] D. Zhang and M. Kamel , Survey of Palmprint Recognition, Pattern
Recognition Vol. 42, pp. 1408 - 1418, (2009).
[2] W. K.Kong, D. Zhang and W. Li , Palmprint Feature Extraction using
2-D Filters, Pattern Recognition, Vol. 36, pp. 2339 - 2347, (2003).
[3] A. Kong and D. Zhang, Orientation Selection Using Modified FCM for
Competitive Code-based Palmprint, Pattern Recognition, Vol. 42, pp.
2841-2849, (2009).
[4] 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).
[5] 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).
[6] 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).
[7] 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).
[8] A. Kong, D. Zhang and M. Kamel, Palmprint Identification using Featurelevel
Fusion, Pattern Recognition, Vol. 39, pp. 478-487, (2006).
[9] 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).
[10] 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).
[11] W. Jia, D.S. Huang and Zhang D., Palmprint Verification based on
Robust Line Orientation Code, Pattern Recognition Vol. 41, pp. 1504-
1513, (2008).
[12] K. Y. E. Wong, G. Sainarayanan and Chekima A., Palmprint Identification
Using Wavelet Energy, International Conference on Intelligent and
Advanced Systems, (2007).
[13] X. Zhou, Y. Peng and M. Yang, Palmprint Recognition Using Wavelet
and Support Vector Machines, PRICAI, LNAI 4099, pp. 385-393, (2006).
[14] 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).
[15] T. Connie, T. Andrew and K. Goh, An Automated Palmprint Recognition
System, Image and Vision Computing, Vol. 23, pp. 501-505, (2005).
[16] M. A. You, and s. Jifeng, Palmprint Recognition Based on 2DPCA Moment
Invariant, Fifth International Conference on Image and Graphics,
(2009).
[17] G. Lu, D. Zhang, K. Wang, Palmprint Recognition Using Eigenpalms
Features, Pattern Recognition Letters, Vol. 24, pp. 1463-1467, (2003).
[18] L. M. Borja and O. Fuentes, Object Detection using Image Reconstruction
with PCA , Image and Vision Computing, Vol. 27, pp. 2-9, (2009).
[19] X. Wu, D. Zhang, K. Wang , Fisherpalm Based Palmprint Recognition,
Pattern Recognition Letters, Vol. 24 , pp. 2829-2838, (2003).
[20] 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).
[21] D. Pertrovska, G. Chollet and Dorizz B., Guide to Biometric Reference
Systems and Performance Evaluation, Springer, (2009).
[22] D. Zhang, poly-U Palmprint Database, Biometric Research Centre,
Hong Kong Polytechnic University, (Online) Available from:
(http://www.comp.polyu.edu.hk/˜biometrics/).
@article{"International Journal of Information, Control and Computer Sciences:54387", author = "Deepti Tamrakar and Pritee Khanna", title = "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.", keywords = "DWT, EER, Euclidean Distance, Gabor filter, PCA,
ROI.", volume = "5", number = "12", pages = "1577-5", }
