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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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Related in: MedlinePlus

Scattering removal experiments. (a) Some captured finger-vein images I(x, y). (b) The estimated scattering components V (x, y). (c) The estimated scattering radiations Ir(x, y). (d) The estimated transmission maps T (x, y). (e) The restored images I0(x, y).
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f9-sensors-12-03627: Scattering removal experiments. (a) Some captured finger-vein images I(x, y). (b) The estimated scattering components V (x, y). (c) The estimated scattering radiations Ir(x, y). (d) The estimated transmission maps T (x, y). (e) The restored images I0(x, y).

Mentions: Here, some captured finger-vein image samples are collected to demonstrate the validity of the proposed method in finger-vein image restoration. Figure 9 shows some examples of the estimated V (x, y), Ir(x, y), T (x, y) and restored finger-vein images I0(x, y). After scattering removal, the contrast of finger-vein images is improved significantly, and the vein networks present in the restored images can be clearly distinguished from the background. This shows that the proposed optical model allowing for the effects of light scattering in skin layer, particularly the multiple scattering, is desirable for describing the mechanism of finger-vein image degradation.


Scattering removal for finger-vein image restoration.

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

Scattering removal experiments. (a) Some captured finger-vein images I(x, y). (b) The estimated scattering components V (x, y). (c) The estimated scattering radiations Ir(x, y). (d) The estimated transmission maps T (x, y). (e) The restored images I0(x, y).
© Copyright Policy
Related In: Results  -  Collection

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

f9-sensors-12-03627: Scattering removal experiments. (a) Some captured finger-vein images I(x, y). (b) The estimated scattering components V (x, y). (c) The estimated scattering radiations Ir(x, y). (d) The estimated transmission maps T (x, y). (e) The restored images I0(x, y).
Mentions: Here, some captured finger-vein image samples are collected to demonstrate the validity of the proposed method in finger-vein image restoration. Figure 9 shows some examples of the estimated V (x, y), Ir(x, y), T (x, y) and restored finger-vein images I0(x, y). After scattering removal, the contrast of finger-vein images is improved significantly, and the vein networks present in the restored images can be clearly distinguished from the background. This shows that the proposed optical model allowing for the effects of light scattering in skin layer, particularly the multiple scattering, is desirable for describing the mechanism of finger-vein image degradation.

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
Related in: MedlinePlus