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. 2012;12(3):3627-40.
doi: 10.3390/s120303627. Epub 2012 Mar 15.

Scattering removal for finger-vein image restoration

Jinfeng Yang  1 , Ben Zhang, Yihua Shi
Affiliations

Scattering removal for finger-vein image restoration

Jinfeng Yang et al. Sensors (Basel). 2012.

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.

Keywords: finger-vein; image restoration; optical model; scattering removal.

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Figures

Figure 1.
Figure 1.
Finger-vein image acquisition system. (a) NIR light transillumination. (b) A homemade finger-vein imaging device. (c) ROI extraction proposed in [4].
Figure 2.
Figure 2.
Image contrast reduction due to light scattering. (a) A real shadow as no light scattering. (b) A degraded shadow as light scattering.
Figure 3.
Figure 3.
Effects of atmospheric scattering.
Figure 4.
Figure 4.
Light propagation through biological tissue.
Figure 5.
Figure 5.
Simplified skin scattering model.
Figure 6.
Figure 6.
Skin layer modeling. (a) Cross-sectional view of human skin. (b) Simplified model of finger palm-side skin layer.
Figure 7.
Figure 7.
Schematic representation of the effect of scattered radiation.
Figure 8.
Figure 8.
POC measure. Left: r(x, y) of two same finger-vein images. Right: r(x, y) of two finger-vein images from different classes.
Figure 9.
Figure 9.
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).
Figure 10.
Figure 10.
Comparisons with other methods. (a) Some captured finger-vein images. (b) The results from histogram template equalization (HTE) [5]. (c) The results from high frequency emphasis filtering (HFEF) [13]. (d) The results from circular Gabor filtering (CGF) [7]. (e) The results from image dehazing (ImD) [19]. (f) The results from the proposed method.
Figure 11.
Figure 11.
ROC curves of different finger-vein enhancement results.
See this image and copyright information in PMC

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