This paper presents a comparative study of watermarking schemes. The embedding of watermark is performed after the image normalization. By normalization process the normalized image achieves invariance properties against geometric attacks which include rotation, scaling and translation of an image. Watermarking is done using five methods DCT Zigzag, DCT blocks, DWT, Zernike transform, SVD-DCT. ...

An approach to a robust reference image watermarking scheme in Discrete Wavelet Transform (DWT) using Singular Value Decomposition (SVD) and edge detection has been proposed. Here the cover image has scrambled and then segmented into number of blocks. Based on number of edges in each block we form a reference image. Then modify the singular values of DWT applied reference image and the watermar...

Iris recognition is one of the most accurate biometric methods in use today. However, the iris recognition algorithms are currently implemented on general purpose sequential processing systems, such as generic central processing units (CPUs). One of the remaining problems in iris recognition is the implementation of its efficient hardware systems. This proposed work uses a hardware Beagleboard-...

Single photon emission computed tomography (SPECT) is an important biomedical imaging modality. However, since gamma cameras are expensive and bulky, truncated projection data are either preferred or unavoidable. Inspired by the recent results on interior tomography in the x-ray CT field, here we present the interior SPECT approach for exact and stable reconstruction of a region of interest (RO...

The state-of-the-art technology for theoretically exact local computed tomography (CT) is to reconstruct an object function using the truncated Hilbert transform (THT) via the projection onto convex sets (POCS) method, which is iterative and computationally expensive. Here we propose to reconstruct the object function using the THT via singular value decomposition (SVD). First, we review the ma...

A major drawback in deploying beamforming scheme in orthogonal frequency division multiplexing (OFDM) is to obtain the optimal weights that are associated with information beams. Two beam weighting methods, namely co-phasing and singular vector decomposition (SVD), are considered to maximize the signal beams for such beamforming scheme. Initially the system performance with and without interlea...

Medical image denoising is the main step in medical diagnosis, which removes the noise without affecting relevant features of the image. There are many algorithms that can be used to reduce the noise such as: threshold and the sparse representation. The K-SVD is one of the most popular sparse representation algorithms, which is depend on Orthogonal Matching Pursuit (OMP) and Discrete Cosine Tra...

This paper presents a new method for exon detection in DNA sequences based on multi-scale parametric spectral analysis. A forward-backward linear prediction (FBLP) with the singular value decomposition (SVD) algorithm FBLP-SVD is applied to the double-base curves (DB-curves) of a DNA sequence using a variable moving window sizes to estimate the signal spectrum at multiple scales. Simulations ar...

Medical image denoising is the main step in medical diagnosis, which removes the noise without affecting relevant features of the image. There are many algorithms that can be used to reduce the noise such as: threshold and the sparse representation. The K-SVD is one of the most popular sparse representation algorithms, which is depend on Orthogonal Matching Pursuit (OMP) and Discrete Cosine Tra...

This paper proposes a novel compression combined digital image watermarking scheme based on singular value replacement technique. Image compression is achieved using Huffman encoding technique. Huffman encoding is an entropy encoding algorithm offering lossless image compression. The proposed watermarking scheme combines Integer wavelet transform (IWT) with singular value decomposition (SVD). F...