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Distance-adaptive thermal infrared face recognition method

A technology adapted to thermal and infrared people, applied in the field of image recognition, can solve the problems of poor generalization ability, difficulty in thermal infrared imaging face recognition, low recognition rate, etc., to facilitate feature extraction, rapid detection and efficient recognition, and image enhancement The effect of details

Active Publication Date: 2022-07-29
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to solve the above-mentioned technical problems, the present invention proposes a distance-adaptive thermal infrared face recognition method, which can effectively solve the problem that thermal infrared imaging is greatly affected by the distance and cause face recognition difficulties when the distance changes. The actual image collected by infrared equipment shows the problem of poor generalization ability and low recognition rate

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  • Distance-adaptive thermal infrared face recognition method
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  • Distance-adaptive thermal infrared face recognition method

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Embodiment 1

[0046] As a basic embodiment of the present invention, the present invention includes a distance adaptive thermal infrared face recognition method, comprising the following steps:

[0047] S 1 .Construct and train the improved thermal infrared image super-resolution enhancement network Retinex-CNN, and use the improved thermal infrared image super-resolution enhancement network Retinex-CNN completed by the training to process the thermal infrared image.

[0048] The improved thermal infrared image super-resolution enhancement network Retinex-CNN includes a decomposition network Decompose-Net and a reflection component denoising enhancement network Enhance-Net. The decomposition network Decompose-Net includes decomposition of reflection components and illumination components of low-light images.

[0049] S 2 .Based on the prior information acquired by near-infrared, according to the invariant feature extraction algorithm, the recognition performance is improved by extracting ...

Embodiment 2

[0051] As a preferred embodiment of the present invention, the present invention includes a distance adaptive thermal infrared face recognition method, comprising the following steps:

[0052] S 1 .Build and train the improved thermal infrared image super-resolution enhancement network Retinex-CNN, including building and training the decomposition network Decompose-Net and building the reflection component denoising enhancement network Enhance-Net.

[0053] The construction and training of the decomposition network Decompose-Net specifically includes the following steps:

[0054] S 11 . Construct a twinned decomposition network Decompose-Net with a depth of 5. The decomposition network Decompose-Net consists of multiple convolutional layers and activation layers.

[0055] S 12 . Respectively convert the normal lighted face image S normal and low-light face images S low Input the decomposition network Decompose-Net, decompose under the guidance of Retinex theory, and obtai...

Embodiment 3

[0062] As another preferred embodiment of the present invention, the present invention includes a distance adaptive thermal infrared face recognition method, comprising the following steps:

[0063] S 1 .Construct and train the improved thermal infrared image super-resolution enhancement network Retinex-CNN, and use the improved thermal infrared image super-resolution enhancement network Retinex-CNN completed by the training to process the thermal infrared image. The improved thermal infrared image super-resolution enhancement network Retinex-CNN includes a decomposition network Decompose-Net and a reflection component denoising enhancement network Enhance-Net. The decomposition network Decompose-Net includes decomposition of low-illumination image reflection components and illumination components;

[0064] S 2 .Based on the prior information obtained by near-infrared, different feature algorithms are used to extract local features from the near-infrared and processed therma...

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Abstract

The invention relates to the technical field of image recognition, in particular to a distance-adaptive thermal infrared face recognition method, which comprises the following steps: constructing and training an improved thermal infrared image super-resolution enhancement network Retinex-CNN, and processing a thermal infrared image by using the trained improved thermal infrared image super-resolution enhancement network Retinex-CNN; on the basis of prior information obtained by near-infrared, different feature algorithms are utilized, local feature extraction is carried out on near-infrared and processed thermal infrared images, full feature fusion is carried out on the extracted different features, dimension reduction processing is carried out on the fused features, and then classification and recognition are carried out on the features after dimension reduction. Through the recognition method, the problem that face recognition is difficult due to the fact that thermal infrared imaging is greatly influenced by the distance when the distance changes can be effectively solved.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a distance adaptive thermal infrared face recognition method. Background technique [0002] Image enhancement is one of the key preprocessing methods in face recognition technology. Aiming at the problem that the resolution of face images is too low due to distance, image enhancement is mainly divided into two categories: indirect methods and direct methods. The indirect method refers to the use of super-resolution algorithm enhancement to indirectly deal with the problem of low resolution. Most super-resolution algorithms aim to improve the visual effect of images, but ignore the recognition rate as an evaluation criterion for image enhancement. The direct method refers to extracting robust face features that can distinguish different faces from low-resolution face images, and can be divided into feature-based and structure-based extraction methods. For example, usi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V40/16G06K9/62G06N3/04G06N3/08G06V10/80G06V10/82
CPCG06V40/168G06V40/172G06V10/806G06V10/82G06N3/08G06N3/045G06F18/253Y02T10/40
Inventor 殷光强李超米尔卡米力江·亚森郑雨晴刘亮
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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