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A Face Image Restoration Method Based on Generative Adversarial Network

A face image and repair method technology, applied in the field of image processing, can solve problems such as limited image repair application scenarios, and achieve the real effect of face images

Active Publication Date: 2021-09-28
NANJING UNIV OF POSTS & TELECOMM
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Traditional image restoration techniques often require specific shapes of defect parts and simple texture repetition, which limits the application scenarios of image restoration

Method used

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  • A Face Image Restoration Method Based on Generative Adversarial Network
  • A Face Image Restoration Method Based on Generative Adversarial Network
  • A Face Image Restoration Method Based on Generative Adversarial Network

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Embodiment Construction

[0044] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0045] Such as figure 1 As shown, the present invention designs a face image restoration method based on a generative confrontation network. In practical applications, it specifically includes the following steps:

[0046] Step A. Collect a large number of images containing complete and clear faces through the existing database or from the Internet, and use them to train the generative confrontation network. OpenFace is a face detection method based on deep neural network. Using this method, the face part in each image is intercepted, and the scale is normalized into a 64×64 pixel image, which is named sequentially by number and saved in the same file. folder, thus constructing a face image database containing 6400 images.

[0047] Step B. Build a generative confrontation network model, including a generator G and a disc...

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Abstract

The invention discloses a face image restoration method based on a generative confrontation network. The method comprises the following steps: (1) collecting a large number of images containing complete and clear faces, and establishing a face image database; (2) constructing a face image database; Generative confrontation network; (3) train the generative confrontation network, optimize the parameters of the generator and discriminator in the generative confrontation network; (4) input the random vector that obeys the normal distribution into the trained generator, Generate a face image, compare the intact area of ​​the face image to be repaired with the corresponding area of ​​the generated image, continuously adjust the input vector until the two are similar, and finally convert the pixels in the blocked or damaged area of ​​the face image to be repaired Values ​​are replaced with the pixel values ​​of the corresponding regions of the generated face image. Aiming at the problem of repairing occluded or damaged face images, the present invention adopts a generative confrontation network with a deep learning structure to effectively solve the problem of image repair in image processing.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a face image restoration method based on a generative confrontation network. Background technique [0002] With the popularity of electronic photographic equipment, digital photos have entered every aspect of people's lives, and image processing has therefore received extensive attention. Image inpainting is an extremely important part of image processing. Image restoration uses the information of the intact part of the image to fill in the occluded, damaged or redundant parts. It can be used to remove the occlusion of photos, repair damaged cultural relic images, image data preprocessing and other fields. [0003] Traditional image inpainting techniques often require specific shapes of defect parts and simple texture repetition, which limits the application scenarios of image inpainting. With the improvement of computer computing power and the maturity of...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06T3/40
CPCG06T3/40G06T5/005G06T2207/20081G06T2207/30201
Inventor 卢官明郝强刘华明毕学慧
Owner NANJING UNIV OF POSTS & TELECOMM