Finger vein biological key generation method based on deep neural network coding

A deep neural network and biological key technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as sensitivity to illumination differences, insufficient key success rate and strength, and insufficient length of stable bit sequences. , to achieve the effect of expanding the scope of application

Pending Publication Date: 2021-06-04
HANGZHOU DIANZI UNIV
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Problems solved by technology

This method can have a certain stabilizing effect on the finger vein feature sequence, but it is limited by the sensitivity of the processing method to the difference in illumination, and the number of stable feature compo

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  • Finger vein biological key generation method based on deep neural network coding
  • Finger vein biological key generation method based on deep neural network coding
  • Finger vein biological key generation method based on deep neural network coding

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Embodiment Construction

[0041] The present invention will be further described below in conjunction with accompanying drawing.

[0042] The process of finger vein bio-key generation based on deep neural network coding is as follows:figure 1 shown. When the finger vein image is taken, the range of motion of the finger is small, the image is deformed, and the range of movement is not large. Therefore, in the preprocessing stage of the finger vein image, it is assumed that the finger vein image matched by the user is close to alignment.

[0043] Finger vein biological key generation method that the present invention proposes comprises the following steps:

[0044] Step (1), multiple sample collections are performed on the same finger vein, generally the number of collections is > 20, and the finger vein grayscale image is obtained; the above finger vein grayscale image is uniformly scaled to a fixed pixel size (generally greater than 80× 160, smaller than 160×320), recorded as finger vein image 1;

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Abstract

The invention discloses a finger vein biological key generation method based on deep neural network coding. By combining a classical finger vein image processing method and a deep neural network processing method of a finger vein original image, compared with an existing classical finger vein feature point extraction method, stable feature components of different samples of the same finger vein can be extracted more accurately, and through layer-by-layer processing of the deep neural network, features are kept to be feature values. finally, through a finger vein fuzzy extractor, high-intensity key sequence generation of a normal finger vein image is realized, and the length of the generated finger vein biological key can be greater than 256 bits. Biological feature template information needing to be recorded does not exist, the risk of privacy disclosure is greatly reduced, meanwhile, a user can generate a high-safety secret key without high-intensity memory, the secret key can be used for existing public and private keys, symmetric encryption and other operations, and the safety and flexibility of finger vein biological feature use are improved.

Description

technical field [0001] The invention belongs to the technical field of information security, and in particular relates to a method for generating a biological key from human finger vein images via deep neural network encoding. The generated key can be used for identity authentication and encryption operation, which can be understood as a kind of ubiquitous encryption technology in network security. Background technique [0002] Compared with other biometric features, finger vein recognition has stronger universality and uniqueness. In vivo recognition, finger surface skin conditions do not affect the recognition work, non-contact collection and other advantages are gradually being valued in the field of local identity authentication. The framework of finger vein recognition is similar to that of the traditional biometric identification technology, both of which adopt the method of obtaining biometric information images first, and finger vein recognition generally uses infrar...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V40/10G06N3/045G06F18/241G06F18/214
Inventor 吴震东
Owner HANGZHOU DIANZI UNIV
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