Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Gray scale video watermarking algorithm based on core tensor

A core tensor and grayscale video technology, applied in image watermarking, computing, computer security devices, etc., can solve problems such as weak robustness and failure to consider the correlation of adjacent video frames, etc., to achieve imperceptibility Effect

Pending Publication Date: 2019-08-09
绍兴聚量数据技术有限公司 +1
View PDF4 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Although the above patents can improve the robustness of watermarking, there is still a problem that the correlation between adjacent frames of the video is not considered, which leads to the problem that the robustness of the algorithm to frame attacks is usually not strong

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Gray scale video watermarking algorithm based on core tensor
  • Gray scale video watermarking algorithm based on core tensor
  • Gray scale video watermarking algorithm based on core tensor

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0057]This embodiment provides a grayscale video watermarking algorithm based on core tensor, such as figure 1 shown, including steps:

[0058] S11. Carrying out Arnold transformation to the video watermark;

[0059] S12. Decompose each video tensor by Tucker and obtain the core tensor;

[0060] S13. Quantify and correct the acquired core tensor;

[0061] S14. Reconstruct the quantized and corrected core tensor to generate a reconstructed watermarked video.

[0062] In this embodiment, a video V whose size is M×N is set first, and the size of the watermark B is m×m. Assuming that each K frame of grayscale video is represented as a third-order tensor, each tensor A i (1≤i≤m 2 ) has a size of M×N×K.

[0063] The method of watermark embedding is as follows: figure 2 shown.

[0064] S11. Carrying out Arnold transformation to the video watermark;

[0065] In order to eliminate the spatial correlation between watermark pixels, use the Arnold transform to scramble the water...

Embodiment 2

[0088] This embodiment provides a grayscale video watermarking algorithm based on core tensor, such as image 3 shown, including steps:

[0089] S11. Carrying out Arnold transformation to the video watermark;

[0090] S12. Decompose each video tensor by Tucker and obtain the core tensor;

[0091] S13. Quantify and correct the acquired core tensor;

[0092] S14. Reconstruct the quantized and corrected core tensor to generate a reconstructed watermarked video;

[0093] S15. Decompose and obtain the core tensor by Tucker for each reconstructed watermarked video;

[0094] S16. Determine watermark information according to the obtained core tensor;

[0095] S17. Obtain original watermark information through Arnold inverse transformation.

[0096] In this embodiment, a video V whose size is M×N is set first, and the size of the watermark B is m×m. Assuming that each K frame of grayscale video is represented as a third-order tensor, each tensor A i (1≤i≤m 2 ) has a size of M×N...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a gray scale video watermarking algorithm based on core tensor. The gray scale video watermarking algorithm comprises the following steps: S11, carrying out Arnold transformation on a video watermark; S12, decomposing each video tensor through Tucker and obtaining a core tensor; S13, quantifying and correcting the obtained core tensor; and S14, reconstructing the quantizedand corrected core tensor to generate a reconstructed watermark video. According to the invention, the grayscale video is represented by three orders as tensors, and the correlation between adjacent frames of the video is fully considered. By quantifying the core tensor, the watermark information is uniformly dispersed into each frame of the video, so that the non-perceptibility of the algorithm and the common video attack are improved.

Description

technical field [0001] The invention relates to the technical field of video watermarking, in particular to a grayscale video watermarking algorithm based on core tensor. Background technique [0002] With the rapid development of the Internet, video acquisition has become increasingly convenient. However, driven by profit, the problem of video piracy is also more rampant. In recent years, digital watermark technology has achieved certain results in the field of video copyright protection. It embeds watermark information into the redundant information of the carrier to protect video copyright. [0003] According to different embedding domains, video watermarking technology can be divided into spatial domain watermarking technology and transform domain watermarking technology. Based on airspace video watermarking technology, Kalker T introduces the idea of ​​spread spectrum into broadcast monitoring, regards video as a series of continuous images, and embeds watermark infor...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06T1/00G06F21/60
CPCG06T1/005G06F21/602
Inventor 李黎张善卿陆剑锋郭小云
Owner 绍兴聚量数据技术有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com