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Z. B. Zhang, D. Y. Wu, S. L. Ma, and J. Ma, (2005) Mul-tiscale feature extraction of finger-vein patterns based on wavelet and local interconnection structure neural net-works and brain,. ICNN&B’05, 2(13-15), 1081-1084.

has been cited by the following article:

• TITLE: Finger-vein image recognition combining modified hausdorff distance with minutiae feature matching

  AUTHORS: Cheng-Bo Yu, Hua-Feng Qin, Lian Zhang, Yan-Zhe Cui

  KEYWORDS: Biometrics; Finger-Vein Verification; Gabor Enhancement; Minutiae Matching; Modified Hausdorff Distance

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.2 No.4, August 17, 2009

  ABSTRACT: In this paper, we propose a novel method for finger-vein recognition. We extract the features of the vein patterns for recognition. Then, the minutiae features included bifurcation points and ending points are extracted from these vein patterns. These feature points are used as a geometric representation of the vein patterns shape. Finally, the modified Hausdorff distance algorithm is provided to evaluate the identifica-tion ability among all possible relative positions of the vein patterns shape. This algorithm has been widely used for comparing point sets or edge maps since it does not require point cor-respondence. Experimental results show these minutiae feature points can be used to perform personal verification tasks as a geometric rep-resentation of the vein patterns shape. Fur-thermore, in this developed method. we can achieve robust image matching under different lighting conditions.