A Method of Image Removal of Logo Based on Generative Adversarial Neural Network

A neural network and station logo technology, applied in the field of image processing, can solve the problems of image deformation, leaving station logo, traces, etc., and achieve the effect of not easy image deformation and good image restoration.

Active Publication Date: 2020-06-09
央视国际网络无锡有限公司
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Problems solved by technology

[0003] Aiming at the deficiencies of the above-mentioned prior art, the present invention provides a method for removing logos from images generated against a neural network, which effectively solves the technical problem in the prior art that the images after the logos are deformed and leave obvious traces of the logos

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  • A Method of Image Removal of Logo Based on Generative Adversarial Neural Network
  • A Method of Image Removal of Logo Based on Generative Adversarial Neural Network
  • A Method of Image Removal of Logo Based on Generative Adversarial Neural Network

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[0055] In order to make the content of the present invention clearer and easier to understand, the content of the present invention will be further described below in conjunction with the accompanying drawings. Of course, the present invention is not limited to this specific embodiment, and general replacements known to those skilled in the art are also covered within the protection scope of the present invention.

[0056] like figure 1 Shown is a schematic flow chart of the method for removing logos from images based on generative adversarial neural networks provided by the present invention. It can be seen from the figure that the method for removing logos from images includes:

[0057] S10 constructing a training data set and a testing data set;

[0058] S20 constructs a generator network, and the generator network is used to generate an image without a station logo according to an input image with a station logo and a station logo mask image;

[0059] S30 constructs a disc...

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Abstract

The invention discloses a method for removing a station logo from an image generated against a neural network, comprising: S10 constructing a training data set and a test data set; S20 constructing a generator network, and the generator network is used for inputting an image with a station logo and a station logo The mask image generates an image without a station logo; S30 builds a discriminator network, which is connected to the output of the generator network, and the discriminator network is used to compare the real image without a station logo and the image without a station logo output by the generator network. True or false judgment; S40 trains the generator network and the discriminator network according to the training data set; S50 uses the trained generator network to perform delabeling operation on the test data set. The obtained generator network has a significantly better effect of removing the logo than the traditional algorithm. In most scenes, there are basically no traces of the logo. The image repair degree is good, and the image deformation is not easy to appear in the repaired area.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image removal method based on a generative confrontational neural network. Background technique [0002] In the field of broadcasting and television, most materials have a logo, but in some application scenarios, the logo needs to be covered or removed due to copyright or other reasons. Traditional methods for removing logos include watershed algorithm, fast marching algorithm (also known as FFM algorithm), etc. Although the processing speed is fast, in most cases, especially in scenes with more background details, the processed image will appear image distortion , there will be obvious traces of the logo. Contents of the invention [0003] Aiming at the deficiencies of the above-mentioned prior art, the present invention provides a method for removing logos from images generated against a neural network, which effectively solves the technical problems in the prior...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06N3/04
CPCG06T5/005G06T2207/20081G06T2207/20084G06N3/045
Inventor 苏许臣朱立松黄建杰
Owner 央视国际网络无锡有限公司
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