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A method for image de-marking base on generating antagonistic neural network

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

Active Publication Date: 2019-03-15
央视国际网络无锡有限公司
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

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

Method used

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  • A method for image de-marking base on generating antagonistic neural network
  • A method for image de-marking base on generating antagonistic neural network
  • A method for image de-marking base on generating antagonistic neural network

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Embodiment Construction

[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] Such as 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 d...

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Abstract

The invention discloses a method for generating an image de-marking of an antagonistic neural network, which comprises the following steps: S10 constructing a training data set and a test data set; S20 constructs a generator network for generating an image without a stage mark according to the input stage mark image and the stage mark mask image; S30, a discriminator network is constructed and connected with the output end of the generator network, and the discriminator network is used for judging the true image without bench mark and the image without bench mark output by the generator network; S40 trains the generator network and the discriminator network according to the training data set; S50 uses the trained generator network to de-label the test data set. The effect of the generatornetwork is obviously better than the traditional algorithm. In most scenes, the residual traces of the marker can not be seen. The image restoration degree is good, and the image distortion is not easy to occur in the restoration 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...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06N3/04
CPCG06T2207/20081G06T2207/20084G06N3/045G06T5/77
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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