Watermark Based on Singular Value Decomposition

نویسندگان

چکیده

Watermarking operation can be defined as a process of embedding special wanted and reversible information in important secure files to protect the ownership or cover file based on proposed singular value decomposition (SVD) watermark. The method for digital watermark has very huge domain constructing final number this mean protecting from conflict. is image need protected. A hidden unique extracted by performing related successive operations, starting dividing original into four various parts with unequal size. Each part these treated separate matrix applying SVD it, diagonal selected determine its norm. norms will processed produce one used developed future exploiting some other features than construct two numbers, each them owned methodology, avoiding challenges changings transformation process.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

پیشنهاد روش جدیدی برای محاسبه polynomial singular value decomposition ) psvd )

در این پایان نامه به معرفی روشهای مختلف محاسبه psvd می پردازیم. بخشی از این روشها به بررسی روشهای مختلف محاسبه psvd در مقالات مطالعه شده می پردازد که می توان به محاسبهpsvd با استفاده از الگوریتمهای pqrd و pevd و sbr2 و محاسبه psvd براساس تکنیک kogbetliantz و روش پارامتریک برای محاسبه psvd اشاره نمود. بخش بعدی نیز به بررسی روشهای مستقیم پیشنهادی محاسبه psvd برای ماتریسهای 2×2و2× n و n×2 و 3× n و...

15 صفحه اول

Singular Value Decomposition based Steganography Technique for JPEG2000 Compressed Images

In this paper, a steganography technique for JPEG2000 compressed images using singular value decomposition in wavelet transform domain is proposed. In this technique, DWT is applied on the cover image to get wavelet coefficients and SVD is applied on these wavelet coefficients to get the singular values. Then secret data is embedded into these singular values using scaling factor. Different com...

متن کامل

Singular Value Decomposition (SVD) and Generalized Singular Value Decomposition (GSVD)

The singular value decomposition (SVD) is a generalization of the eigen-decomposition which can be used to analyze rectangular matrices (the eigen-decomposition is definedonly for squaredmatrices). By analogy with the eigen-decomposition, which decomposes a matrix into two simple matrices, the main idea of the SVD is to decompose a rectangular matrix into three simple matrices: Two orthogonal m...

متن کامل

Robust Singular Value Decomposition

The singular value decomposition of a rectangular data matrix can be used to understand the structure of the data and give insight into the relationships of the row and column factors. For example, the rows linked to the rows might be experimental conditions of temperature and the experimental conditions linked to the columns might pressure. In a biological setting the rows might be linked to t...

متن کامل

The Singular Value Decomposition

Carlo Tomasi Any m n matrix of rank r transforms the unit sphere in Rn into an r-dimensional hyperellipsoid in Rm. For instance, the rank-2 matrix A = 1 p2 264 p3 p3 3 3 1 1 375 (1) transforms the unit circle on the plane into an ellipse embedded in three-dimensional space. Figure 1 shows the map y = Ax : Two diametrically opposite points on the unit circle are mapped into the two endpoints of ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Baghdad Science Journal

سال: 2023

ISSN: ['2078-8665', '2411-7986']

DOI: https://doi.org/10.21123/bsj.2023.7168