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ROI Extraction and Enhancement for Finger Vein Recognition
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 Title & Authors
ROI Extraction and Enhancement for Finger Vein Recognition
Lee, Ju-Won; Lee, Byeong-Ro;
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Recently, the finger vein recognition based on NIR and CCD sensor camera is investigating the technology to identify a personal using by biometrics. The performance difference of finger vein recognition is generated according to methods that are to separate the vein and background from noises such as finger thickness, ambient light, skin temperature, etc. To improve these problems, in this study, we are proposing the methods for rotation, ROI extraction, and enhancement of vein image captured by NIR LED and CCD camera, and were evaluated performances of these methods. In results of the experiment, the accuracy of the proposed method for image rotation and ROI extraction was 99.8%. And the proposed filter bank method in vein enhancement has shown better performance than retinex algorithm. The proposed method for results of these experimentations will provide better recognition rate when applied to the preprocessing of finger vein recognition.
Finger vein recognition;ROI extraction;filter bank;Vein enhancement;
 Cited by
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Jain A, Ross A, Prabhakar S, An Introduction to Biometric Recognition, IEEE Trans. Circuits Syst. Video Technol. Vol. 14, No. 4, 2004.

U. Uludag, S. Pankanti, S. Prabhakar, and A. K. Jain, Biometric cryptosystems: issues and challenges, Proc. of the IEEE, vol. 92, pp. 948-960, 2004. crossref(new window)

Lingyu wang, G. Leedham, Gray-Scale Skeletonization of Thermal Vein Patterns Using the Watershed Algorithm in Vein Pattern Biometrics, International Conference Computational Intelligence and ecurity, Vol. 2, pp. 1597-1602, 2006.

Tong Liu, Jianbin Xie, Huanzhang Lu, Wei Yan, Peiqin Li, A Threshold Image Method for Finger-vein Segmentation, Applied Mechanics and Materials Vols. 263-266, pp. 2439-2442, 2013.

Naoto Miura, Akio Nagasaka, Extraction of finger-vein patterns using Maximim Curvature Points in Image Profiles, IAPR Conference on Machine Vision Applications, May 16-18, pp. 347-350, 2005.

Truc, P., Khan, M.A., Lee, Y., Lee, S., Kim, T.: Vessel enhancement filter using directional filter bank. Comput. Vis. and Image Under., Vol. 113, pp. 101-112, 2009. crossref(new window)

Zhang J, Yang J, Finger-vein Image Enhancement Based on Combination of Gray-level Grouping and Circular Gabor Filter, Proceedings of the International Conference on Information Engineering and Computer Science, 2009.

Yang, J.F., Yang, J.L., Shi, Y.H.: Finger-vein segmentation based on multi-channel even-symmetric Gabor filter. ICIS, Vol. 4, pp. 500-503, 2009.

Cho S R, Park Y H, Nam G P, Shin K Y, Lee H C, Park K R, Kim S M, Kim H C, Enhancement of Finger-vein Image by Vein Line Tracking and Adaptive Gabor Filtering for Finger vein Recognition, Applied Mechanics and Materials. Vol. 145, pp. 219-223, 2012.

Naoto Miura, Akio Nagasaka, Takafumi 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. 5, pp. 194-203, 2004. crossref(new window)

M. Khalil-Hani, P.C. Eng, Personal Verification using Finger Vein Biometrics in FPGA-based System-on-Chip, ELECO International Conference on Electrical and Electronics Engineering, 1-4 December, Bursa, TURKEY, pp. 151-156, 2011.

Biomedical Image Group,Local Normalization, Filter to reduce the effect on a non-uniform illumination [Internet]. Available:

Rahman, Z.-U.; Jobson, D.J.; Woodell, G.A. Retinex Processing for Automatic Image Enhancement. J. Electron. Imaging, Vol. 13, pp.100-110. 2004. crossref(new window)

Hua-Bin Wang, and Liang Tao, Novel Algorithm for Enhancement of Hand Vein Images based on Adaptive Filtering and Retinex Method, Proceedings of the IEEE International Conference on Information Science and Technology (ICIST), Wuhan, Hubei, China, pp. 857-860, 23-25 March, 2012.