Finger vein recognition algorithm under reduced field of view

Abstract

Algorithms for finger vein recognition methods are generally designed based on greyscale images containing vein distributions, but greyscale inhomogeneities and non-venous texture structures often adversely affect the recognition results. Besides, the performance of the algorithm when the field of view is reduced has not been studied. Therefore, the aim of this paper is to propose an algorithm based on binary image, so as to minimize the interference of non-venous factors in the identification process. We use the feature from accelerated segment test algorithm to detect feature points, and use gradient histogram to describe these feature points in a vectorized manner. In addition, we propose the concept of circular matching neighbourhood, and select the matching feature point pairs in this area. Then, the Euclidean distance and the number of correct matching pairs were comprehensively considered to increase the recognition rate of the algorithm. The algorithm was tested on the database of SDU-MLA, FV-USM and MMCBNU-6000. The results show that the algorithm has certain advantages before and after the field of view is reduced. Therefore, this paper not only provides a new idea for finger vein recognition, but also has practical application value for the miniaturization of finger vein acquisition devices.