Finger vein recognition method by interested areas and directional elements

A region of interest and finger vein technology, applied in character and pattern recognition, instruments, calculations, etc., can solve the problems of large amount of calculation, large amount of calculation, and low recognition rate of single vein feature, and achieve anti-noise and image geometric deformation , the effect of high recognition accuracy

Inactive Publication Date: 2013-09-18
HEILONGJIANG UNIV
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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.

Method used

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  • Finger vein recognition method by interested areas and directional elements
  • Finger vein recognition method by interested areas and directional elements
  • Finger vein recognition method by interested areas and directional elements

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0043] A finger vein recognition method for regions of interest and directional elements. First, the region of interest is extracted by using the region of interest extraction method based on rotation correction for the read finger vein image, and then the gradient size of the pixel points on the finger vein pattern is used to extract the region of interest. and direction construction vector to characterize the direction feature of the vein pattern in the region of interest, and combine the direction feature with the degree of membership of the image sub-block to construct the feature vector of the vein image; finally in the finger vein matching stage , using the cross-correlation coefficient to measure the similarity of different linear feature vectors to obtain the matching result.

Embodiment 2

[0045] According to the finger vein recognition method of ROI and directional elements described in Embodiment 1, in the ROI extraction method based on rotation correction, the finger vein image is first rotated and corrected before the ROI is extracted. Based on the different parts of the finger to the near-infrared light penetrating ability to extract the region of interest in the image, the specific method is as follows:

[0046] (1) Rotation correction:

[0047] Perform rotation correction through the center of mass of the foreground area of ​​the image, and calculate the center of mass of the target image, that is, the image of the finger area, after taking out the finger area , its calculation formula is as follows:

[0048]

[0049]

[0050]

[0051] in, Indicates the first The abscissa of pixels, Indicates the first The ordinate of the element, Indicates the width of the image, Indicates the height of the image, Indicates the region belonging to ...

Embodiment 3

[0061] According to the finger vein recognition method of the region of interest and the direction element described in embodiment 1 or 2, the region of interest should be located in the same region on all finger vein images, and the main vein information should exist in this region, And in order to further register during matching, we need to extract stable reference elements from the finger vein image as a suitable reference point to locate the image and extract the region of interest to reduce the rotation caused by the sampling process , translation, distortion and other nonlinear factors.

[0062] (1) Rotation correction

[0063] Since the non-contact collection method is more friendly, the finger vein image library of the present invention adopts a non-contact collection method. Since no positioning device is used in this collection method, the position and direction of the finger of the collector are somewhat different. There are different degrees of rotation and trans...

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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...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46
Inventor 马慧孙书利王科俊
Owner HEILONGJIANG UNIV
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