Restoration of finger vein image based on multiple scattering model

Abstract

Abstract: To improve the restoration quality of finger vein images and better describe the propagation characteristics of photons in skin tissue, a multiple scattering model is proposed by adopting GGD as convolution kernel to approximately describe the diffusion characteristics of photons during transmission and attenuation process in skin tissue. Then maximum filter and anisotropic diffusion filter are used to estimate the background lighting, and the transmission map is obtained by Laplacian sharpening and high lifting filter. MSSIM index is introduced to evaluate the quality of finger vein image restoration. Experiment results indicate that the proposed algorithm can effectively improve the restoration quality of finger vein images.

Key words: finger vein image, image restoration, multiple scattering, generalized Gaussian distribution function, laplacian sharpening

CLC Number:

TP391

YANG Jinfeng, ZHANG Xirui. Restoration of finger vein image based on multiple scattering model[J]. Journal of Civil Aviation University of China, 2020, 38(3): 55-60.

References 19

[1]	余成波, 秦华锋. 生物特征识别技术：手指静脉识别技术[M]. 北京:清华大学出版社, 2009.
[2]	刘建科, 李洋. 针对光照不均的低对比度手指静脉增强[J]. 微电子学与计算机, 2012, 29(12): 91-93.
[3]	李洪兵, 余成波, 张冬梅, 等. 基于脊波变换的手指静脉图像增强研究[J]. 重庆邮电大学学报（自然科学版）, 2011, 23(2): 224-230.
[4]	张军, 游林, 孙磊. 基于top-hat 变换的手指静脉图像增强算法[J]. 南阳理工学院学报, 2012, 4(4): 48-51.
[5]	高晓燕, 马军山, 吴佳杰. 手指静脉图像增强算法研究[J]. 光学仪器,2010, 32(4): 29-32.
[6]	SHIN K Y, PARK Y H, NGUYEN D T, et al. Finger-vein image enhancement using a fuzzy -based fusion method with gabor and retinex filtering[J]. Sensors, 2014, 14(2): 3095.
[7]	崔建江, 李琦, 薛定宇, 等. 基于皮肤散射模型的手指静脉图像去模糊化[J]. 光学精密工程, 2016, 24(10): 727-732.
[8]	LEE E C, KANGR P. Image restoration of skin scattering and optical blurring for finger vein recognition[J]. Optics & Lasers in Engineering,2011, 49(7): 816-828.
[9]	YANG JINFENG, WANG JUNJIE. Finger-vein image restoration considering skin layer structure [C]//International Conference on Hand-Based Biometrics, Hong Kong, China, NOV17-18, 2011: 1-5.
[10]	YANG JINFENG, ZHANG BEN, SHI YIHUA. Scattering removal for finger-vein image restoration[J]. Sensors, 2012, 12(3): 3627-3640.
[11]	YANG JINFENG, BAI GUANGLIANG. Finger-vein image restoration based on skin optical property[C]//IEEE, International Conference on Signal Processing, Beijing, China, Oct 21-25, 2013: 749-752.
[12]	YANG JINFENG, SHI YIHUA. Towards finger-vein image restoration and enhancement for finger-vein recognition[J]. Information Sciences,2014, 268(6): 33-52.
[13]	PRASAD P N. Bioimaging：principles and techniques[M]. Hoboken:John Wiley & Sons, Inc., 2004: 203-254.
[14]	HOLLIS V S, BINZONI T, DELPY D T. Noninvasive monitoring of brain tissue temperature by near-infrared spectroscopy[C]//Proceedings of the SPIE, 2001, 4250: 470-481.
[15]	NARASIMHAN S G, NAYAR S K. Vision and the atmosphere[J]. International Journal of Computer Vision, 2002, 48(3): 233-254.
[16]	NARASIMHAN S G, NAYAR S K. Shedding Light on the Weather[C]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003: 665-672.
[17]	METARI S, DESCHENES F. A new convolution kernel for atmospheric point spread function applied to computer vision[C]//IEEE, International Conference on Computer Vision, Rio de Janeiro, Brasil, Oct 14-21, IEEE, 2007: 1-8.
[18]	WANG Z, BOVIK A C, SHEIKHH R, et al. Image quality assessment:from error visibility to structural similarity[J]. IEEE Transactions on Image Processing, 2004, 139(4): 600-612.
[19]	WEI P, SHIN J, PARK D. An effective quality improvement approach for low qualityfingervein image[C]//International ConferenceonElectronics and Information Engineering, Ryoto, Japan, Aut 1-3, IEEE, 2010,1: 424-427.