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Scattering removal for finger-vein image restoration.

Yang J, Zhang B, Shi Y - Sensors (Basel) (2012)

Bottom Line: To give a proper description of finger-vein image degradation, a biological optical model (BOM) specific to finger-vein imaging is proposed according to the principle of light propagation in biological tissues.Based on BOM, the light scattering component is sensibly estimated and properly removed for finger-vein image restoration.Finally, experimental results demonstrate that the proposed method is powerful in enhancing the finger-vein image contrast and in improving the finger-vein image matching accuracy.

View Article: PubMed Central - PubMed

Affiliation: Tianjin Key Laboratory for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China. jfyang@cauc.edu.cn

ABSTRACT
Finger-vein recognition has received increased attention recently. However, the finger-vein images are always captured in poor quality. This certainly makes finger-vein feature representation unreliable, and further impairs the accuracy of finger-vein recognition. In this paper, we first give an analysis of the intrinsic factors causing finger-vein image degradation, and then propose a simple but effective image restoration method based on scattering removal. To give a proper description of finger-vein image degradation, a biological optical model (BOM) specific to finger-vein imaging is proposed according to the principle of light propagation in biological tissues. Based on BOM, the light scattering component is sensibly estimated and properly removed for finger-vein image restoration. Finally, experimental results demonstrate that the proposed method is powerful in enhancing the finger-vein image contrast and in improving the finger-vein image matching accuracy.

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ROC curves of different finger-vein enhancement results.
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f11-sensors-12-03627: ROC curves of different finger-vein enhancement results.

Mentions: For finger-vein matching on this database, the number of genuine attempts is 3,150 , and the number of impostor attempts is 241,500 . By respectively using the original images, HTE-based images, HFEF-based images, CGF-based images, ImD-based images and the proposed restored images for finger-vein matching under POC (Phase-Only-Correlation) measure, the ROC (receiver operating characteristic) curves are plotted in Figure 11, where false non-match rates (FNMR) and false match rates (FMR) are shown in the same plot at different thresholds on the POC matching score, and EER (equal error rate) is the error rate where FNMR and FMR are equal.


Scattering removal for finger-vein image restoration.

Yang J, Zhang B, Shi Y - Sensors (Basel) (2012)

ROC curves of different finger-vein enhancement results.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3376557&req=5

f11-sensors-12-03627: ROC curves of different finger-vein enhancement results.
Mentions: For finger-vein matching on this database, the number of genuine attempts is 3,150 , and the number of impostor attempts is 241,500 . By respectively using the original images, HTE-based images, HFEF-based images, CGF-based images, ImD-based images and the proposed restored images for finger-vein matching under POC (Phase-Only-Correlation) measure, the ROC (receiver operating characteristic) curves are plotted in Figure 11, where false non-match rates (FNMR) and false match rates (FMR) are shown in the same plot at different thresholds on the POC matching score, and EER (equal error rate) is the error rate where FNMR and FMR are equal.

Bottom Line: To give a proper description of finger-vein image degradation, a biological optical model (BOM) specific to finger-vein imaging is proposed according to the principle of light propagation in biological tissues.Based on BOM, the light scattering component is sensibly estimated and properly removed for finger-vein image restoration.Finally, experimental results demonstrate that the proposed method is powerful in enhancing the finger-vein image contrast and in improving the finger-vein image matching accuracy.

View Article: PubMed Central - PubMed

Affiliation: Tianjin Key Laboratory for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China. jfyang@cauc.edu.cn

ABSTRACT
Finger-vein recognition has received increased attention recently. However, the finger-vein images are always captured in poor quality. This certainly makes finger-vein feature representation unreliable, and further impairs the accuracy of finger-vein recognition. In this paper, we first give an analysis of the intrinsic factors causing finger-vein image degradation, and then propose a simple but effective image restoration method based on scattering removal. To give a proper description of finger-vein image degradation, a biological optical model (BOM) specific to finger-vein imaging is proposed according to the principle of light propagation in biological tissues. Based on BOM, the light scattering component is sensibly estimated and properly removed for finger-vein image restoration. Finally, experimental results demonstrate that the proposed method is powerful in enhancing the finger-vein image contrast and in improving the finger-vein image matching accuracy.

Show MeSH