Digital watermarking is one of the techniques for copyright protection. In this paper, a normalization-based robust image watermarking scheme which encompasses singular value decomposition (SVD) and discrete cosine transform (DCT) techniques is proposed. For the proposed scheme, the host image is first normalized to a standard form and divided into non-overlapping image blocks. SVD is applied t...

A novel watermarking technique using Singular Value Decomposition (SVD) and non-sinusoidal column/row transforms like Haar, Walsh, Slant and Discrete Kekre Transform is proposed in the paper. Host images are subject to column/row transform using orthogonal non-sinusoidal transforms and watermark is subjected to SVD. To prevent loss of watermark after performing attacks on watermarked image, wat...

This paper highlights the extension of dwt-svd based image watermarking to medical images. In recent times internet has become a primary source of communication between the diagnostics center and the remote doctor located at some hospital. With the use of internet come the problem of data authenticity and the responsibility of the medical practitioner to preserve sensitive information of patien...

We present a variation to the well studied SVD based image compression technique. Our variation can be viewed as a preprocessing step in which the input image is permuted as per a fixed, data independent permutation, after which it is fed to the standard SVD algorithm. Likewise, our decompression algorithm can be viewed as the standard SVD algorithm followed by a postprocessing step which appli...

The Singular Value Decomposition (SVD) has many applications in image processing. The SVD can be used to restore a corrupted image by separating significant information from the noise in the image data set. This thesis outlines broad applications that address current problems in digital image processing. In conjunction with SVD filtering, image compression using the SVD is discussed, including ...

Time series stored as feature vectors can be indexed by multidimensional index trees like R-Trees for fast retrieval. Due to the dimensionality curse problem, transformations are applied to time series to reduce the number of dimensions of the feature vectors. Different transformations like Discrete Fourier Transform (DFT), Discrete Wavelet Transform (DWT), Karhunen-Loeve (KL) transform or Sing...

Aiming at rolling bearing fault diagnosis, the collected vibration signal contains complex noise interference, and one-dimensional information cannot be used to fully mine data features of problem. This paper proposes a diagnosis method based on SVD-GST combined with Vision Transformer. Firstly, is preprocessed reduce using singular value decomposition (SVD) obtain more accurate useful signal. ...

In recent years, digital image watermarking has gained a significant amount of popularity and developed into crucial essential tool for copyright protection, security, the identification multimedia content. Despite its high computational complexity, singular value decomposition (SVD) is an extensively utilized transformation in watermarking. This research presents robust blind scheme that direc...