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.
Highlights
Biometrics is the science of identifying a person using their physiological or behavioral features
Dubuisson and Jain [12] developed several modified Hausdorff distances (MHD) for comparing the edge maps computed from the gray-scale images
Experimental results indicate that these minutiae feature points can be used to perform personal verification tasks as a geometric representation of the vein patterns shape
Summary
Biometrics is the science of identifying a person using their physiological or behavioral features. Guo et al proposed a new modified Hausdorff distance which is weighted by a function derived from the spatial information of human face [15]. Lin et al proposed modified Hausdorff distances with spatial weighting determined by eigenface features [16]. Zhu et al employed an improved Gabor filter for computing edge maps and applied a weighted modified Hausdorff distance (WMHD) in a circular Gabor feature space for comparing images [17]. LingyuWanga applied the modified Hausdorff distance based matching scheme to the interesting points for comparing images [6]. Experimental results indicate that these minutiae feature points can be used to perform personal verification tasks as a geometric representation of the vein patterns shape. We are able to achieve robust image matching under different lighting conditions
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