Hand Vein Image Enhancement With Radon Like Features Descriptor
Nowadays, hand vein recognition has attracted more attentions in identification biometrics systems. Generally, hand vein image is acquired with low contrast and irregular illumination. Accordingly, if you have a good preprocessing of hand vein image, we can easy extracted the feature extraction even with simple binarization. In this paper, a proposed approach is processed to improve the quality of hand vein image. First, a brief survey on existing methods of enhancement is investigated. Then a Radon Like features method is applied to preprocessing hand vein image. Finally, experiments results show that the proposed method give the better effective and reliable in improving hand vein images.
[1] Jing Zhang and Jinfeng Yang, Finger-Vein Image Enhancement Based on
Combination of Gray-Level Grouping and Circular Gabor Filter, International
Conference on Information Engineering and Computer Science,
2009.
[2] Andinet Enquobahrie and Luis Ibanez, Vessel Enhancing Diffusion Filter,
Insight Journal, 2007.
[3] Jinfeng Yang and Minfu Yan, An Improved Method for Finger-vein Image
Enhancement, IEEE 10th International Conference on Signal Processing
(ICSP), 2010.
[4] Daugman, J. G. Uncertainty relation for resolution in space, spatial
frequency, and orientation optimized by two-dimensional visual cortical
filters, Journal of the Optical Society of America, 1985.
[5] Jianwei Yang, Lifeng Liu, Tianzi Jiang and Yong Fan, A modified
Gabor filter design method for fingerprint image enhancement, Pattern
Recognition Letters, pp.1805- 1817 (2003).
[6] L. Ma, T. Tan, Y. Wang and D. Zhang, Personal identification based
on iris texture analysis, IEEE Trans. on Pattern Analysis and Machine
Intelligence, 2003.
[7] David Zhang, Wai Kin Kong, On Line Palmprint Identification, IEEE
Transactions on Pattern Analysis and Machine Intelligence, 2003.
[8] J. Zhao, X. Xiong, L. Zhang, T. Fu and Y. Zhao, Study on enhanced
algorithm of hand vein image based on CLAHE and Top-hat transform,
Chinese journal of Laser and Nfrared, pp. 220-222, 2009.
[9] Seungjoon Yang, Jae Hwan Oh, and Yungjun Park, Contrast enhancement
using histogram equalization with bin underflow and bin overflow,
International Conference on Image Processing (ICIP), 2003.
[10] Ritwik Kumar, Amelio Vazquez-Reina and Hanspeter Pfister, Radon-
Like Features and their Application to Connectomics, IEEE Computer
Society Conference on Computer Vision and Pattern Recognition Workshops
(CVPRW), 2010.
[11] Hand vein database is available to "http://bosphorus.ee.boun.edu.tr/".
[12] R.M. Haralick , Statistical and structural approachs to texture, Proceedings
of the IEEE In Proceedings of the IEEE 67 (1979), 786-804.
[1] Jing Zhang and Jinfeng Yang, Finger-Vein Image Enhancement Based on
Combination of Gray-Level Grouping and Circular Gabor Filter, International
Conference on Information Engineering and Computer Science,
2009.
[2] Andinet Enquobahrie and Luis Ibanez, Vessel Enhancing Diffusion Filter,
Insight Journal, 2007.
[3] Jinfeng Yang and Minfu Yan, An Improved Method for Finger-vein Image
Enhancement, IEEE 10th International Conference on Signal Processing
(ICSP), 2010.
[4] Daugman, J. G. Uncertainty relation for resolution in space, spatial
frequency, and orientation optimized by two-dimensional visual cortical
filters, Journal of the Optical Society of America, 1985.
[5] Jianwei Yang, Lifeng Liu, Tianzi Jiang and Yong Fan, A modified
Gabor filter design method for fingerprint image enhancement, Pattern
Recognition Letters, pp.1805- 1817 (2003).
[6] L. Ma, T. Tan, Y. Wang and D. Zhang, Personal identification based
on iris texture analysis, IEEE Trans. on Pattern Analysis and Machine
Intelligence, 2003.
[7] David Zhang, Wai Kin Kong, On Line Palmprint Identification, IEEE
Transactions on Pattern Analysis and Machine Intelligence, 2003.
[8] J. Zhao, X. Xiong, L. Zhang, T. Fu and Y. Zhao, Study on enhanced
algorithm of hand vein image based on CLAHE and Top-hat transform,
Chinese journal of Laser and Nfrared, pp. 220-222, 2009.
[9] Seungjoon Yang, Jae Hwan Oh, and Yungjun Park, Contrast enhancement
using histogram equalization with bin underflow and bin overflow,
International Conference on Image Processing (ICIP), 2003.
[10] Ritwik Kumar, Amelio Vazquez-Reina and Hanspeter Pfister, Radon-
Like Features and their Application to Connectomics, IEEE Computer
Society Conference on Computer Vision and Pattern Recognition Workshops
(CVPRW), 2010.
[11] Hand vein database is available to "http://bosphorus.ee.boun.edu.tr/".
[12] R.M. Haralick , Statistical and structural approachs to texture, Proceedings
of the IEEE In Proceedings of the IEEE 67 (1979), 786-804.
@article{"International Journal of Information, Control and Computer Sciences:57488", author = "Randa Boukhris Trabelsi and Alima Damak Masmoudi and Dorra Sellami Masmoudi", title = "Hand Vein Image Enhancement With Radon Like Features Descriptor", abstract = "Nowadays, hand vein recognition has attracted more attentions in identification biometrics systems. Generally, hand vein image is acquired with low contrast and irregular illumination. Accordingly, if you have a good preprocessing of hand vein image, we can easy extracted the feature extraction even with simple binarization. In this paper, a proposed approach is processed to improve the quality of hand vein image. First, a brief survey on existing methods of enhancement is investigated. Then a Radon Like features method is applied to preprocessing hand vein image. Finally, experiments results show that the proposed method give the better effective and reliable in improving hand vein images.
", keywords = "Hand Vein, Enhancement,Contrast, RLF, SDME", volume = "7", number = "6", pages = "788-4", }
