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A finger vein recognition method based on image super-resolution

A technology of super-resolution and recognition methods, applied in character and pattern recognition, instruments, computer components, etc., can solve the problems of poor recognition effect, high false detection rate of finger vein recognition, blurred images, etc., and achieve faster Reconstruction speed, improve accuracy and processing speed, avoid the effects of real-time effects

Active Publication Date: 2019-06-25
ZHEJIANG SCI-TECH UNIV
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AI Technical Summary

Problems solved by technology

If the image quality is not good, even if the recognition algorithm has a strong matching ability, the recognition effect will not be very good
At present, the finger vein image is collected by irradiating the finger with an infrared CCD camera, and the collected image is relatively blurred, resulting in a very high false detection rate of the final finger vein recognition.

Method used

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  • A finger vein recognition method based on image super-resolution
  • A finger vein recognition method based on image super-resolution
  • A finger vein recognition method based on image super-resolution

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Embodiment Construction

[0052] The present invention will be described in detail below in conjunction with the accompanying drawings and specific implementation, but not as a limitation to the invention.

[0053] 1. Method

[0054] like figure 1 , the implementation steps of this method are as follows:

[0055] A collection of finger vein images

[0056] The finger is irradiated by infrared light, and the image of the finger vein is obtained by the CCD camera, and the image of the finger vein is obtained as follows: figure 2 shown.

[0057] B reconstructed high-resolution finger vein image

[0058] The network architecture of the image super-resolution model is as follows: image 3 As shown, firstly, initialize the image super-resolution model, read the parameter file, analyze the model structure, and load the model weight.

[0059] The image super-resolution model extracts image structural features such as Figure 4 As shown, the finger vein image obtained in step A is input into the low-fre...

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Abstract

The invention discloses a finger vein recognition method based on image super-resolution reconstruction, and relates to the fields of biological recognition technology, computer vision, machine learning and the like. The method comprises the following steps: S10, acquiring a finger vein image; S20, reconstructing a high-resolution finger vein image; S30, performing image preprocessing; S40, extracting finger vein line characteristics; And S50, storing the finger vein features to a database to realize finger vein recognition. An image super-resolution reconstruction technology is applied to thefield of finger vein recognition, a universal and efficient finger vein recognition algorithm is designed, and the speed and accuracy of finger vein recognition can be effectively improved by improving the resolution of a finger vein image.

Description

technical field [0001] The invention relates to the fields of biometric identification technology, computer vision, machine learning and the like. Specifically, it relates to a finger vein recognition method based on image super-resolution. Background technique [0002] With the development of information technology, there are more and more demands on the market to use identity authentication technology to identify a person. The method of using traditional identity documents (such as personal ID cards, work permits, driver's licenses, savings cards, etc.) to verify identity has been far from guaranteeing the security and reliability of identification. The shortcomings of traditional identity authentication technology cannot meet the needs of identity authentication, and more agile and reliable biometric technology needs to be adopted. Among them, the finger vein recognition technology not only uses in vivo features that are difficult to be copied, but also belongs to livin...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06K9/46
Inventor 张娜高春波包晓安陈春宇黄友
Owner ZHEJIANG SCI-TECH UNIV
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