Image watermarking embedding and extracting method based on singular value decomposition and principal component analysis

A technology of principal component analysis and singular value decomposition, applied in image data processing, image data processing, instruments, etc., can solve problems such as poor imperceptibility, complex training samples, and large amount of computation

Inactive Publication Date: 2015-05-06
HENAN NORMAL UNIV
View PDF1 Cites 23 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to overcome the problems of poor imperceptibility and weak robustness, large amount of calculation and low precision in the existing methods of image waterm

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
  • Image watermarking embedding and extracting method based on singular value decomposition and principal component analysis
  • Image watermarking embedding and extracting method based on singular value decomposition and principal component analysis
  • Image watermarking embedding and extracting method based on singular value decomposition and principal component analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0073] Embodiments of the present invention provide further detailed descriptions of the present invention below in conjunction with the accompanying drawings.

[0074] Considering the security of the image watermark, the present invention uses the singular value decomposition and principal component analysis technology of the image matrix to propose an image watermark embedding and extraction method based on the singular value decomposition and principal component analysis. The image is scrambled, and the number of keys is increased to improve the security of the watermark; then the image is subjected to singular value decomposition (SVD), and the singular value obtained has quite good stability. When the image is slightly disturbed, its singular value The value will not change drastically, so that the correct detection of the watermark can be realized, and the image watermark embedding and extraction method with excellent robustness against conventional image attacks is reali...

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 an image watermarking embedding method based on singular value decomposition and principal component analysis. The method includes: S1a, conducting scrambling processing on the original watermarking image W and obtaining the scrambled watermarking image W' ; S2a, conducting blocking on an original carrier image I, dividing the original carrier image I into an image block C of 8X8 and further obtaining original carrier image blocks; S3a, conducting the singular value decomposition on the original carrier image blocks C and obtaining the singular value of each image block; S4a, taking the singular value of each image block as the eigenvalue of the principal component analysis, conducting the principal component analysis on the singular value, extracting the component Y of the principal component whose the contribution rate reaches above 99.99%; and S5a, embedding watermarks in the component Y of the principal component, obtaining the component Y' of the principal component embedded with the watermarking image information, conducting inverse transformations of the principal component analysis and the singular value decomposition on Y', and obtaining the carrier image I' embedded with the watermarking.

Description

technical field [0001] The invention relates to a digital image watermark technology in the field of information security, in particular to an image watermark embedding and extraction method based on singular value decomposition and principal component analysis. Background technique [0002] As an effective supplement to traditional encryption methods, digital image watermarking technology uses data embedding methods to hide in digital image products to prove the creator's ownership of his works, and as a basis for identification and prosecution of illegal infringement. Detection and analysis to ensure the integrity and reliability of digital information has become an effective means of intellectual property protection and digital multimedia anti-counterfeiting. For image watermarking to play its due role, it must have two basic elements: robustness and imperceptibility. Watermark robustness means that the embedded image watermark still has good detectability after digital ...

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): G06T1/00
Inventor 孙林闫娟申长安刘国奇王振华徐久成袁培燕张恩宋黎明董婉
Owner HENAN NORMAL UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap