[1] Zhao S, Wang B, Tang C Y. Arm vein feature extraction and matching based on chain code[J]. Acta Optica Sinica, 36, 0515003(2016).

[2] Kirbas C, Quek F. A review of vessel extraction techniques and algorithms[J]. ACM Computing Surveys, 36, 81-121(2004). http://dl.acm.org/citation.cfm?id=1031121

[3] Fraz M M, Remagnino P, Hoppe A. et al. Blood vessel segmentation methodologies in retinal images - a survey[J]. Computer Methods and Programs in Biomedicine, 108, 407-433(2012). http://dl.acm.org/citation.cfm?id=2365739

[4] Otsu N. A threshold selection method from gray-level histograms[J]. IEEE Transactions on Systems, Man, and Cybernetics, 9, 62-66(1979). http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4310076

[5] Joardar S, Chatterjee A, Rakshit A. Real-time NIR imaging of Palm Dorsa subcutaneous vein pattern based biometrics: An SRC based approach[J]. IEEE Instrumentation & Measurement Magazine, 19, 13-19(2016). http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=7462787

[6] Lajevardi S M, Arakala A, Davis S et al. Hand vein authentication using biometric graph matching[J]. IET Biometrics, 3, 302-313(2014). http://ieeeexplore.com/stamp/stamp.jsp?tp=&arnumber=6985833

[7] Martinez-Perez M E, Hughes A D, Thom S A et al. . Improvement of a retinal blood vessel segmentation method using the Insight Segmentation and Registration Toolkit (ITK)[C]. Engineering in Medicine and Biology Society, 892-895(2007).

[8] Chaudhuri S, Chatterjee S, Katz N et al. Detection of blood vessels in retinal images using two-dimensional matched filters[J]. IEEE Transactions on Medical Imaging, 8, 263-269(1989). http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=34715

[9] Hoover A D, Kouznetsova V, Goldbaum M. Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response[J]. IEEE Transactions on Medical imaging, 19, 203-210(2000). http://europepmc.org/articles/PMC2232087

[10] Liu I, Sun Y. Recursive tracking of vascular networks in angiograms based on the detection-deletion scheme[J]. IEEE Transactions on Medical Imaging, 12, 334-341(1993). http://europepmc.org/abstract/med/18218423

[11] Sun Y. Automated identification of vessel contours in coronary arteriograms by an adaptive tracking algorithm[J]. IEEE Transactions on Medical Imaging, 8, 78-88(1989). http://europepmc.org/abstract/MED/18230503

[12] Miura N, Nagasaka A, Miyatake T. Feature extraction of finger-vein patterns based on repeated line tracking and its application to personal identification[J]. Machine Vision and Applications, 15, 194-203(2004). http://onlinelibrary.wiley.com/doi/10.1002/scj.10596/citedby

[13] Yin Y, Adel M, Bourennane S. Automatic segmentation and measurement of vasculature in retinal fundus images using probabilistic formulation[J]. Computational and Mathematical Methods in Medicine, 2013, 260410(2013). http://europepmc.org/abstract/med/24382979

[14] Yin Y, Adel M, Bourennane S. Retinal vessel segmentation using a probabilistic tracking method[J]. Pattern Recognition, 45, 1235-1244(2012). http://dl.acm.org/citation.cfm?id=2108053

[15] Tolias Y A, Panas S M. A fuzzy vessel tracking algorithm for retinal images based on fuzzy clustering[J]. IEEE Transactions on Medical Imaging, 17, 263-273(1998). http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=700738

[16] Nayebifar B, Moghaddam H A. A novel method for retinal vessel tracking using particle filters[J]. Computers in Biology and Medicine, 43, 541-548(2013). http://europepmc.org/abstract/MED/23434235

[17] Rao A R, Jain R C. Computerized flow field analysis: Oriented texture fields[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14, 693-709(1992).

[18] Zhang J, Li H, Nie Q et al. A retinal vessel boundary tracking method based on Bayesian theory and multi-scale line detection[J]. Computerized Medical Imaging and Graphics, 38, 517-525(2014). http://europepmc.org/abstract/med/24974011

[19] Qin X W, Cai C, Zhou C P. An algorithm for removing burr of skeleton[J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 32, 28-31(2004).

[20] Martin D R, Fowlkes C C, Malik J. Learning to detect natural image boundaries using local brightness, color, and texture cues[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26, 530-549(2004). http://europepmc.org/abstract/MED/15460277