About image digital watermark embedded strength regression prediction model modeling method

A technology of digital watermarking and embedding strength, applied in the field of information security, can solve problems affecting the robustness and concealment of digital watermarking, poor robustness and concealment of digital watermarking, and inability to accurately control the embedding strength of digital watermarking, etc. The effect of eliminating blocking, improving robustness and stealth

Inactive Publication Date: 2017-10-10
GUANGDONG KINGPOINT DATA SCI & TECH CO LTD
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Problems solved by technology

However, in the prior art, the watermarking algorithm is used to directly embed the digital watermark into the image. In this process, since there is no reference model for the embedding strength of the digital watermark, the embedding strength of the digital watermark cannot be accurately controlled. Usually less robust and s

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  • About image digital watermark embedded strength regression prediction model modeling method
  • About image digital watermark embedded strength regression prediction model modeling method
  • About image digital watermark embedded strength regression prediction model modeling method

Examples

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Embodiment Construction

[0031] The present invention will be further described in detail below through specific implementations:

[0032] The embodiment is basically as shown in the figure: the image digital watermark embedding system disclosed in this embodiment is as figure 1 As shown, it includes a machine learning module 10, an input module 20, a watermark embedding module 30, and an output module 40.

[0033] The machine learning module 10 is used to establish a regression prediction model on the embedding strength of the watermark using SVM to realize the prediction of the best embedding strength of the watermark for the original image to be embedded, and includes a preprocessing unit 101 and a machine learning unit 102. The preprocessing unit is used to establish a data set, the data set includes a training set and a test set, and the digital watermark embedding is performed on all the images in the data set one by one, and a corresponding optimal watermark embedding strength is determined for each...

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Abstract

The invention discloses an image digital watermark embedded strength regression prediction model modeling method. The method herein includes the following steps: firstly setting watermark evaluation parameters which include a similarity NC which is intended for balancing watermark robustness and a peak signal-to-noise ratio which is intended for balancing watermark concealment, and based on requirements, determining a weight [beta] between two parameters, and using the SVM method to conduct machine learning on a training set. The method herein establishes a regression prediction model related to watermark embedded strength, can predict optimal watermark embedded strength of a to-be-embedded original image, and eventually uses DWT conversion to embed digital watermark to the original image.

Description

Technical field [0001] The invention relates to the technical field of information security, in particular to a modeling method of an image digital watermark embedding strength regression prediction model. Background technique [0002] With the rapid development of information technology, information security issues have become increasingly prominent. Digital watermarking technology has become a research hotspot in the field of digital product copyright protection by embedding watermark information into digital products (including multimedia, documents, software, etc.) to identify the source of digital products, creators and other copyright information. To achieve the function of copyright protection, digital watermarks should have two characteristics: one is robustness, which means that after signal processing (including channel noise, clipping, rotation, etc.), digital watermarks can maintain partial integrity and can be extracted And identification; the second is concealment,...

Claims

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Application Information

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IPC IPC(8): G06T1/00
CPCG06T1/0021G06T2201/005
Inventor 邹立斌李青海侯大勇简宋全
Owner GUANGDONG KINGPOINT DATA SCI & TECH CO LTD
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