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Finger vein machine learning recognition method and device based on terrain concave-convex characteristics

A machine learning and recognition method technology, applied in neural learning methods, character and pattern recognition, instruments, etc., can solve the difficulty of finger vein feature extraction and feature comparison technology, high-efficiency optimization, and poor recognition of low-quality finger vein images. And other issues

Active Publication Date: 2020-09-08
TOP GLORY TECH INC CO LTD
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AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problem that the existing finger vein technology has poor recognition effect on low-quality finger vein images, and at the same time solve the problem that the existing finger vein feature extraction and feature comparison technology is difficult to achieve high-efficiency optimization. Finger vein machine learning recognition method and device for terrain concave-convex characteristics

Method used

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  • Finger vein machine learning recognition method and device based on terrain concave-convex characteristics
  • Finger vein machine learning recognition method and device based on terrain concave-convex characteristics
  • Finger vein machine learning recognition method and device based on terrain concave-convex characteristics

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Experimental program
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Effect test

Embodiment 1

[0088] combined with figure 1 As shown, a finger vein machine learning recognition method based on terrain bump characteristics, including the following steps:

[0089] 1) Use finger vein equipment to collect registered finger vein images and verify finger vein images. The size of the collected images is 360*180. Bilinear interpolation technology is used to normalize the size of the finger vein images. The selected normalized The row number picH=120 of the normalized image, the column number picW=60 of the selected normalized image;

[0090] 2) Use bilateral filtering to perform image enhancement processing on the normalized registration finger vein image and verification finger vein image respectively, and the calculation formula is:

[0091]

[0092]

[0093] Among them, ω is the weighting coefficient of bilateral filtering, w(x, y) is the spatial kernel, is the value range kernel;

[0094] In this embodiment, taking two pixels (a, b) and (i, j) as an example, the ...

Embodiment 2

[0167] refer to Figure 4 As shown, the present embodiment relates to a finger vein machine learning recognition device based on terrain concave-convex characteristics, including:

[0168] 1) Normalization processing module: used to collect registered finger vein images and verified finger vein images, and perform size normalization processing respectively; the normalization processing module is used to implement step 1) of Embodiment 1.

[0169] 2) Image enhancement module: used to perform image enhancement processing on the normalized registration finger vein image and verification finger vein image; the image enhancement module is used to implement step 2) of the first embodiment.

[0170] 3) feature extraction module: used to obtain the terrain bump feature from the enhanced registration finger vein image and verification finger vein image, extract the registration feature of the registration finger vein image and the verification feature of the verification finger vein im...

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Abstract

The invention relates to a finger vein machine learning recognition method and device based on terrain concave-convex characteristics. The method comprises the steps of performing size normalization processing on a registered finger vein image and a verified finger vein image; performing image enhancement processing on the registered finger vein image and the verified finger vein image; obtainingterrain concave-convex features from the registered finger vein image and the verified finger vein image based on a digital elevation model, and extracting registration features and verification features; translation and rotation calibration correction are carried out on the registration features and the verification features, and sliding window similarity calculation is carried out on an overlapping region of the vein features after calibration correction; optimizing the feature extraction technical parameters and the recognition technical parameters of the finger vein based on the calibration correction parameters and the sliding window similarity parameters; the device comprises a normalization processing module, an image enhancement module, a feature extraction module, a parameter calculation module and an optimization module. According to the method, the technical capability of finger vein recognition and the adaptability to different image qualities are improved.

Description

technical field [0001] The present invention relates to the technical field of image recognition and processing, and in particular to a finger vein machine learning recognition method and device based on terrain concave-convex characteristics. Background technique [0002] Finger vein recognition technology has become one of the biometric technologies with the most development potential due to its advantages of natural non-contact, internal features, and living body recognition. The key technologies of finger vein recognition are divided into feature extraction technology of finger veins and feature comparison technology of finger veins. Currently commonly used finger vein feature extraction technologies include: finger vein skeleton line extraction technology, finger vein feature point extraction technology and finger vein binary extraction technology. Quality finger vein images have poor adaptability. Existing finger vein feature extraction and recognition technology suc...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/32G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V40/1359G06V40/1388G06V10/245G06V10/757G06N3/045
Inventor 张烜赵国栋辛传贤李学双
Owner TOP GLORY TECH INC CO LTD
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