- About this Journal ·
- Abstracting and Indexing ·
- Aims and Scope ·
- Annual Issues ·
- Article Processing Charges ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Recently Accepted Articles ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
Journal of Biomedicine and Biotechnology
Volume 2012 (2012), Article ID 324249, 9 pages
Finger Vein Recognition Based on (2D)2 PCA and Metric Learning
School of Computer Science and Technology, Shandong University, Jinan 250101, China
Received 22 February 2012; Accepted 19 March 2012
Academic Editor: Sabah Mohammed
Copyright © 2012 Gongping Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- J. Yang and M. Yan, “An improved method for finger-vein image enhancement,” in Proceedings of the IEEE 10th International Conference on Signal Processing (ICSP '10), pp. 1706–1709, Beijing, China, October 2010.
- C.-B. Yu, D.-M. Zhang, and H.-B. Li, “Finger vein image enhancement based on multi-threshold fuzzy algorithm,” in Proceedings of the 2nd International Congress on Image and Signal Processing (CISP '09), pp. 1–3, Tianjin, China, October 2009.
- J. F. Yang and J. L. Yang, “Multi-channel gabor filter design for finger vein image enhancement,” in Proceedings of the 5th International Conference on Image and Graphics (ICIG '09), pp. 87–91, Xi'an, China, September 2009.
- N. Miura, A. Nagasaka, and T. Miyatake, “Feature extraction of finger-vein patterns based on repeated line tracking and its application to personal identification,” Machine Vision and Applications, vol. 15, no. 4, pp. 194–203, 2004.
- W. Song, T. Kim, H. C. Kim, J. H. Choi, H. J. Kong, and S. R. Lee, “A finger-vein verification system using mean curvature,” Pattern Recognition Letters, vol. 32, no. 11, pp. 1541–1547, 2011.
- Q. Huafeng, Q. Lan, and Y. Chengbo, “Region growth-based feature extraction method for finger vein recognition,” Optical Engineering, vol. 50, no. 2, pp. 281–307, 2011.
- J. D. Wu and C. T. Liu, “Finger-vein pattern identification using principal component analysis and the neural network technique,” Expert Systems with Applications, vol. 38, no. 5, pp. 5423–5427, 2011.
- J. Yang, D. Zhang, A. F. Frangi, and J. Y. Yang, “Two-dimensional PCA: a new approach to appearance-based face representation and recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 1, pp. 131–137, 2004.
- D. Zhang and Z. H. Zhou, “(2D)2 PCA: two-directional two-dimensional PCA for efficient face representation and recognition,” Neurocomputing, vol. 69, no. 1–3, pp. 224–231, 2005.
- Z. Liu, Y. Yin, H. Wang, S. Song, and Q. Li, “Finger vein recognition with manifold learning,” Journal of Network and Computer Applications, vol. 33, no. 3, pp. 275–282, 2010.
- J. D. Wu and C. T. Liu, “Finger-vein pattern identification using SVM and neural network technique,” Expert Systems with Applications, vol. 38, no. 11, pp. 14284–14289, 2011.
- K. Weinberge, J. Blitzer, and L. Saul, “Distance metric learning for large margin nearest neighbor classification,” in Proceedings of the Advances in Neural Information Processing Systems (NIPS '06), 2006.
- B. Huang, Y. Dai, R. Li, D. Tang, and W. Li, “Finger-vein authentication based on wide line detector and pattern normalization,” in Proceedings of the 20th International Conference on Pattern Recognition (ICPR '10), pp. 1269–1272, Istanbul, Turkey, August 2010.
- J. Yang and X. Li, “Efficient finger vein localization and recognition,” in Proceedings of the 20th International Conference on Pattern Recognition (ICPR '10), pp. 1148–1151, Istanbul, Turkey, August 2010.
- X. Qian, S. Guo, X. Li, F. Zhong, and X. Shao, “Finger-vein recognition based on the score level moment invariants fusion,” in Proceedings of the International Conference on Computational Intelligence and Software Engineering (CiSE '09), pp. 1–4, Wuhan, China, December 2009.
- C. Liukui and Z. Hong, “Finger vein image recognition based on tri-value template fuzzy matching,” in Proceedings of the 9th WSEAS International Conference on Multimedia Systems and Signal Processing (MUSP '09), pp. 206–211, Hangzhou, China, May 2009.
- N. V. Chawla, K. W. Bowyer, L. O. Hall, and W. P. Kegelmeyer, “SMOTE: synthetic minority over-sampling technique,” Journal of Artificial Intelligence Research, vol. 16, pp. 321–357, 2002.