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Visible sensation characteristic based video watermark process

A video watermarking and visual feature technology, applied in digital video signal modification, television, image data processing, etc., can solve the problems of not relying on visual features, low computational complexity, and few video watermarking methods

Inactive Publication Date: 2007-10-31
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This type of scheme has the advantage of low computational complexity, but it is at the expense of local control over the embedding position and limiting the strength of watermark embedding. Essentially, this type of scheme does not depend on visual features and cannot be based on video visual features. Variations come from adapting to embedding watermarks of appropriate strength; another class of schemes proposes a selective distribution of watermark energy in space, but such schemes usually consider MPEG-2 coding structure more than visual characteristics
[0004] At present, the existing video watermarking algorithms still have certain deficiencies in the watermarking technology that relies on the consistency of video features and human visual perception systems, and there are even fewer video watermarking methods with statistical characteristics that can be widely applied on the Internet.

Method used

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  • Visible sensation characteristic based video watermark process
  • Visible sensation characteristic based video watermark process
  • Visible sensation characteristic based video watermark process

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0134] The object to add watermark is color Football video (8bpp), the video frame size is 352×240, the embedded watermark information is 216 bytes of character information, and the corresponding binary watermark information is w k ∈ {-1, 1} (k=1, 2, . . . , 1782). The original video frame before the watermark is added to the Football video is shown in Figure 5(a), and the corresponding video frame after the watermark is added is shown in Figure 5(b). The peak signal-to-noise ratio (PSNR) value of the video frame before and after the watermark is 45.82 dB, the correlation value of watermark detection is 41.521, which is greater than the threshold 6, indicating that the watermark information is detected correctly. The concrete steps that this example implements in detail below in conjunction with the method of the present invention are as follows:

[0135] (1) The watermark embedding steps are as follows:

[0136] ① Debug the watermark information into 0, 1 binary series, dec...

Embodiment 2

[0172] The object to add watermark is the color FlowerGarden video (8bpp), the video frame size is 352×240, the embedded watermark information is 216 bytes of character information, and the corresponding binary watermark information is w k ∈ {-1, 1} (k=1, 2, . . . , 1782). The original video frame of F1owerGarden video before adding watermark is shown in Figure 6(a), and the corresponding video frame after adding watermark is shown in Figure 6(b). The peak signal-to-noise ratio (PSNR) value of the video frame before and after adding watermark is 44.68 dB, the correlation value of watermark detection is 41.377, which is greater than the threshold 6, indicating that the watermark information is detected correctly. . The concrete steps that this example implements in detail below in conjunction with the method of the present invention are as follows:

[0173] (1) The watermark embedding steps are as follows:

[0174] ① Debug the watermark information into a binary series of 0 ...

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Abstract

The invention discloses a video watermark method based on vision characteristic, the method is based on discrete cosine transform technique, and firstly the video frame is discrete cosine transformed to pick up characteristics such as veins, brightness and edge of sub block; then picking up the movement characteristic of video frame to construct a mixed self adapting sub block characteristic adopting model; at last, according to dual requirements of vision sensitivity speciality and watermark robustness, constructing a characteristic Stat constringency model to generate self adapting video watermark method which is accordant with vision sensing model of human. The veins, brightness and edge of sub block and movement characteristic picked up in the invention expresses the vision characteristic, depend on dual requirements of vision sensitivity speciality and watermark robustness, the embedded energy of watermark is refined further, the relative watermark embedding course of video watermark and video vision characteristic is realized, problem of deficient robustness when video watermark technique is applied is resolved.

Description

technical field [0001] The invention relates to the technical field of multimedia digital watermarking, in particular to a video watermarking method based on visual features. Background technique [0002] MPEG is currently the mainstream format for video encoding. With the further popularization of the Internet and the advent of the 3G era, online video will be widely popular. Therefore, watermark protection for MPEG video files has wide application value. Video clips usually contain rich visual features. In order to realize the copyright protection of massive Internet-oriented data, the visual features of the video itself must be effectively utilized. Due to the huge amount of data, this requires that the watermarking algorithm should have certain statistical characteristics, so that it can be applied to most video clips. [0003] Most existing video watermarking schemes including MPEG adopt the idea of ​​extending watermark energy to all pixels in a frame. This type of ...

Claims

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Application Information

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IPC IPC(8): H04N7/26H04N7/30G06T1/00H04N19/467H04N19/625
Inventor 庄越挺吴飞吴国民
Owner ZHEJIANG UNIV
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