Finger vein recognition method by interested areas and directional elements

Abstract

The invention discloses a finger vein recognition method by interested areas and directional elements. Existing vein recognition algorithms can be divided into two types, namely local feature utilization and global feature utilization, but the problems of long time consumption, large computing capacity and low image quality cannot be solved simultaneously. The method includes firstly reading a finger vein image, extracting an interested area by the interested area extraction method based on rotation correction, then constructing vectors by adopting gradient magnitude and direction of pixel points on finger vein lines to represent direction feature of the vein lines in the interested area, combining the direction feature and membership degree of image sub-blocks, creating feature vectors of the vein image, finally during the finger vein matching process, measuring similarity of different linear feature vectors by adopting cross-correlation coefficient, and figuring out matching results. The method is used for finger vein recognition.

Description

Technical field: [0001] The invention relates to a finger vein recognition method for interest regions and direction elements. Background technique: [0002] Vein recognition technology uses the distribution of human subcutaneous veins for identification. In addition to uniqueness, universality and stability, it is not easily affected by the external environment. It has many advantages such as high precision, fast speed, and non-contact. It has become an effective means of identification. Existing vein recognition algorithms can be divided into two types using local features and global features: in the prior art, local feature point matching method is used for vein recognition, and the effect is better, but due to the exhaustive coordinate matching operation, it is time-consuming. The method of pixel point comparison for vein matching also has the problem of a large amount of calculation; some use the endpoints of vein patterns as feature points, and some use the bifurcatio...

AI Technical Summary

Problems solved by technology

Existing vein recognition algorithms can be divided into two types using local features and global features: in the prior art, local feature point matching method is used for vein recognition, and the effect is better, but due to the exhaustive coordinate matching operation, it is time-consuming. The method of pixel point comparison for vein matching also has the problem of a large amount of calculation; some use the endpoints of vein patterns as feature points, and some use the bifurcation points of vein patterns as feature points for Matching, these two algorithms have faster recognition speed, but are greatly affected by image quality

In the method of using global features, some people also fuse the seven invariant moments of vein images as the features to be identified; or use the method of principal component analysis to achieve the purpose of dimensionality reduction matching of vein features, in order to overcome the single vein The feature recognition rate is not high. There is also a combination of principal component analysis and ridgelet transformation for vein recognition. The recognition effect is good, but the amount of calculation is large.

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