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Vein recognition method based on riesz wavelet and sslm model

A technology of vein recognition and model, applied in the field of image recognition

Inactive Publication Date: 2019-05-03
CIVIL AVIATION UNIV OF CHINA
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  • Description
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Problems solved by technology

First, finger vein detection requires a living body. Finger vein images can only be obtained when detecting a living body, which is very safe; second, finger veins are a feature of the body, and external factors will not cause obstacles to recognition. Good anti-interference; Third, everyone's finger vein images are different, unique and irreplaceable

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  • Vein recognition method based on riesz wavelet and sslm model
  • Vein recognition method based on riesz wavelet and sslm model
  • Vein recognition method based on riesz wavelet and sslm model

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[0074] The vein recognition method based on Riesz wavelet and SSLM model provided by the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0075] The vein recognition method based on Riesz wavelet and SSLM model provided by the invention comprises the following steps carried out in order:

[0076] 1) Normalize each original finger vein image collected to 2 m ×2 m Rectangular image of size;

[0077] 2) Perform N-order Riesz transformation on each of the above-mentioned normalized finger vein images to obtain N+1 Riesz transformation images. The transformation formula adopted by Riesz transformation is shown in formula (1):

[0078]

[0079] where R N Represents the N-order Riesz transform, which is composed of N+1 single-core R (n，N-n) Composition; the calculation formula of Riesz single core is shown in formula (2):

[0080]

[0081]

[0082] In the formula, w is the frequency, from the h...

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Abstract

A vein recognition method based on Riesz wavelet and SSLM model. The feature extraction in this method is based on Riesz wavelet. The Riesz transform is a multi-dimensional extension of the Hilbert transform, which has good spectrum directionality and no change in amplitude before and after the transform. The Riesz wavelet combined with the wavelet not only maintains the original directionality, but also increases the characteristic of scale invariance. Using Riesz wavelet to process vein images can effectively extract texture features in different directions and scales. In addition, the SSLM model can use the smallest possible hypersphere to surround the positive sample points, and at the same time use a larger interval to separate the negative sample points, so that the model construction can often be completed with fewer negative samples; and its hypersphere center can be It can better represent positive samples and can generate texture signatures of multiple scales, so the method of the present invention has the characteristics of fast speed, good effect, and strong physical meaning.

Description

technical field [0001] The invention belongs to the technical field of image recognition, in particular to a vein recognition method based on Riesz wavelet and SSLM model. Background technique [0002] Modern biometric identification technology is developing in the direction of accuracy, security, and speed, while traditional biometric identification, such as fingerprints and voices, have long been unable to meet people's needs for security. As a new type of biometric identification technology, finger vein has many advantages over traditional methods. First, finger vein detection requires a living body. Finger vein images can only be obtained when detecting a living body, which is very safe; second, finger veins are a feature of the body, and external factors will not cause obstacles to recognition. Good anti-interference; Third, each person's finger vein images are different, unique and irreplaceable. Contents of the invention [0003] In order to solve the above proble...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06V40/10G06V40/14G06V10/449G06F18/214
Inventor 杨金锋卫建泽师一华
Owner CIVIL AVIATION UNIV OF CHINA
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