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Anti-screen-shooting text image watermark embedding and extracting method based on deep learning

A text image and watermark embedding technology, applied in neural learning methods, image data processing, image data processing, etc., can solve the problems that watermark information is easily affected by the screen capture process, extraction accuracy is low, and text image texture is not considered.

Pending Publication Date: 2022-06-21
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

However, these algorithms do not consider the simple texture of text images, the watermark information is easily affected by the screen capture process, and the extraction accuracy is low, so it cannot be applied to real scenes

Method used

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  • Anti-screen-shooting text image watermark embedding and extracting method based on deep learning
  • Anti-screen-shooting text image watermark embedding and extracting method based on deep learning
  • Anti-screen-shooting text image watermark embedding and extracting method based on deep learning

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Embodiment Construction

[0031] The accompanying drawings constituting a part of the present invention are used to provide further understanding of the present invention, and the exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention.

[0032] like figure 1 As shown, the method of the present invention comprises the steps:

[0033] The method adopted in the present invention is as figure 1 shown, including the following steps:

[0034] (1) Prepare a text image set suitable for deep learning training and testing, in which the training set and test set are required to be different from each other to ensure the independence of the test set.

[0035] (2) Put the text image samples in the training set into batches figure 1 In the framework shown, the training against the screen shot text image watermarking model is carried out, and a text image watermarking model is trained by u...

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Abstract

The invention discloses an anti-screen-shooting text image watermark embedding and extracting method based on deep learning. The method specifically comprises the following steps: step 1, preparing a training set and a test set; 2, establishing a screen shooting text image watermark resisting model; 3, training the screen shooting text image watermark resisting model; 4, inputting the images in the test set into the screen shooting resistant text image watermark model trained in the step 3 one by one, and detecting the accuracy of the model; and step 5, inputting a carrier image which needs to be subjected to watermark embedding into the trained screen shooting resistant text image watermark model to obtain the carrier image after watermark embedding and watermark information. The method provided by the invention has the characteristics of high watermark capacity, high robustness and strong practicability. In the actual use process, the cost is lower, the detection precision is higher, and the consumed time is shorter.

Description

technical field [0001] The invention belongs to the field of digital media copyright protection. Background technique [0002] With the acceleration of the commercialization process, the frequent occurrence of trade secret leaks has led to more and more attention to the source tracking of trade secrets. For traditional ways of stealing information, such as scanning and emailing commercial documents or copying electronic documents, one can track the source of the leak by using traditional robust image watermarking schemes. However, with the popularity of smartphones, filming has become the easiest and most efficient way to transmit information, bringing new challenges to leak source tracking. Anyone with access to the file (such as an authorized employee) can simply reveal the information by taking a photo without leaving any records. The anti-screenshot text image watermarking scheme can be used as a strong guarantee for leak source tracking. We can embed information such...

Claims

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Application Information

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IPC IPC(8): G06T1/00G06F21/16G06N3/04G06N3/08G06K9/62G06V10/774
CPCG06T1/0021G06F21/16G06N3/08G06T2201/0065G06N3/045G06N3/048G06F18/214
Inventor 夏志华葛苏龙徐勇余佩鹏
Owner NANJING UNIV OF INFORMATION SCI & TECH
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