Check patentability & draft patents in minutes with Patsnap Eureka AI!

Structure self-adaptive and structure keeping image local distortion method

A locally distorted and self-adaptive technology, applied in image data processing, graphics and image conversion, instruments, etc., can solve problems such as perceptual distortion, straight edge bending, discomfort, etc.

Inactive Publication Date: 2014-05-14
SHANDONG UNIV OF SCI & TECH
View PDF2 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, neither of these two categories of methods takes into account the structure of the attacked image
Therefore, when applied to images with regular structures such as artificial scenes, it will cause perceptually obvious distortions. For example, for pixels located on the same edge, if the displacement along the direction of the vertical edge is inconsistent, the original straight edge can become curved, causing perceptual distortion and even discomfort, which severely limits its attack effectiveness

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
  • Structure self-adaptive and structure keeping image local distortion method
  • Structure self-adaptive and structure keeping image local distortion method
  • Structure self-adaptive and structure keeping image local distortion method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0076] Overall technical scheme of the present invention is as figure 1 shown. Firstly, an initial offset field is generated, and an existing RBA or LPCD offset vector field can also be used as the initial offset field. Then analyze the local structure of the image to be attacked, and obtain the edge direction e and consistency coefficient κ at each pixel position. For the offset vector d=(d at each pixel position x , d y ) for direction decomposition, and decomposes into components along the edge direction d e and the component d along the vertical edge direction f . Next, for the component d along the edge direction e Smooth with a directional smoothing filter to obtain the smoothed d e weight Finally, the offset vector is reconstructed to complete the smoothing of the initial offset field according to the image structure. Use the smoothed offset field to attack the image, and obtain the image after attack. So far, the entire offset field design and local distortio...

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 structure self-adaptive and structure keeping image local distortion method. The method comprises the steps that under the condition of a single scale, the local edge direction and the local consistency of an image are analyzed firstly, a direction smoothing kernel function is designed accordingly, direction smoothing is conducted on an edge component of an initial biased field through the direction smoothing kernel function, and finally the image is distorted through the smoothed biased field. In order to keep a large-scale structure and a small-scale structure at the same time, a multi-scale image pyramid and a biased field pyramid are constructed, the biased fields are smoothed from top to bottom, iteration smoothing is conducted on the biased fields on each layer so that the smoothing effect can be improved, and each smoothed biased field on the former layer is used as the initial biased field of the biased fields on the next layer. According to the structure self-adaptive and structure keeping image local distortion method, the perception remarkable structural information in the image is analyzed and utilized, so that the effect that the image can be distorted without changing the type of important structures is achieved, the subjective perceived quality of the distorted image is improved, and the attack effect of the distorted image on a watermark system and the like is not influenced.

Description

technical field [0001] The invention relates to a method for locally distorting an image or a video frame and causing it to produce imperceptible geometric deformation, which is a structure-adaptive and structure-preserving image local distortion method, which is applicable to the fields of digital watermark system testing, digital image tampering and evidence collection system testing, etc. . Background technique [0002] Due to the rapid development of multimedia signal processing technology and the convenience of using commercial image processing software such as photoshop, the infringement of digital works such as images, videos and audios has become easier and easier to tamper with, resulting in a series of copyright Dispute issue. Digital watermark technology is an effective means to protect the copyright of digital works. It embeds secret information such as watermark into the digital carrier signal to be protected by embedding algorithm. When a copyright dispute oc...

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
IPC IPC(8): G06T3/00
Inventor 颜斌杨红梅崔鑫郭银景王卓鹏郝建军王凤瑛张同军张仁彦
Owner SHANDONG UNIV OF SCI & TECH
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More