Nazeer Muhammad

Digital image watermarking using partial pivoting lower and upper triangular decomposition into the wavelet domain

A digital image watermarking algorithm using partial pivoting lower and upper triangular (PPLU) decomposition is proposed. In this method, a digital watermark image is factorised into lower triangular, upper triangular and permutation matrices by PPLU decomposition. The permutation matrix is used as the valid key matrix for authentication of the rightful ownership of the watermark image. The product of the lower and upper triangular matrices is embedded into particular sub-bands of a cover image that is decomposed by wavelet transform using the singular value decomposition. The weightage-based differential evolution algorithm is used to achieve the possible scaling factor for obtaining the maximum possible robustness against various image processing operations and pirate attacks. The authors experiments show that the proposed algorithm is highly reliable with better imperceptibility of the embedded image and computationally efficient compared with recently existed methods.

Blind data hiding technique using the Fresnelet transform.

AbstractA new blind data hiding scheme is proposed in which data is decomposed using the Fresnelet transform. The inverse Fresnelet transform is performed on decomposed subbands by choosing different key parameters, and the coded pattern of the information data is obtained. This coded pattern is embedded into particular subbands of the cover image using the wavelets. The proposed method has good imperceptibility and large capacity of the information embedded data. Using the Fresnelet transform with a family of wavelet transforms makes the scheme more efficient in terms of extracted accuracy of hidden information. Moreover, the hidden data can be recovered without access to the original cover data. The proposed method is used to resolve privacy and security issues raised with respect to emerging internet applications for the effective handling of confidential data.

Reversible integer wavelet transform for blind image hiding method

In this article, a blind data hiding reversible methodology to embed the secret data for hiding purpose into cover image is proposed. The key advantage of this research work is to resolve the privacy and secrecy issues raised during the data transmission over the internet. Firstly, data is decomposed into sub-bands using the integer wavelets. For decomposition, the Fresnelet transform is utilized which encrypts the secret data by choosing a unique key parameter to construct a dummy pattern. The dummy pattern is then embedded into an approximated sub-band of the cover image. Our proposed method reveals high-capacity and great imperceptibility of the secret embedded data. With the utilization of family of integer wavelets, the proposed novel approach becomes more efficient for hiding and retrieving process. It retrieved the secret hidden data from the embedded data blindly, without the requirement of original cover image.

A REVIEW ON STATE-OF-THE-ART FACE RECOGNITION APPROACHES

Automatic Face Recognition (FR) presents a challenging task in the field of pattern recognition and despite the huge research in the past several decades; it still remains an open research problem. This is primarily due to the variability in the facial images, such as non-uniform illuminations, low resolution, occlusion, and/or variation in poses. Due to its non-intrusive nature, the FR is an attractive biometric modality and has gained a lot of attention in the biometric research community. Driven by the enormous number of potential application domains, many algorithms have been proposed for the FR. This paper presents an overview of the state-of-the-art FR algorithms, focusing their performances on publicly available databases. We highlight the conditions of the image databases with regard to the recognition rate of each approach. This is useful as a quick research overview and for practitioners as well to choose an algorithm for their specified FR application. To provide a comprehensive survey, the paper divides the FR algorithms into three categories: (1) intensity-based, (2) video-based, and (3) 3D based FR algorithms. In each category, the most commonly used algorithms and their performance is reported on standard face databases and a brief critical discussion is carried out.

On Forgotten Topological Indices of Some Dendrimers Structure

A series of previously conducted experiments pertaining to various chemicals and drugs uncover a natural linkage between the molecular structures and the bio-medical and pharmacological characteristics. The forgotten topological index computed for the molecular structures of various chemical compounds and drugs has proven significant in medical and pharmaceutical fields by predicting biological features of new chemical compounds and drugs. A topological index can be considered as the transformation of chemical structure into a real number. Dendrimers are highly-branched star-shaped macromolecules with nanometer-scale dimensions. Dendrimers are defined by three components: a central core, an interior dendritic structure (the branches), and an exterior surface with functional surface groups. In this paper, we determine forgotten topological indices of poly(propyl) ether imine, porphyrin, and zinc–porphyrin dendrimers.

Sphingosine 1-Phosphate Receptor Modulator Fingolimod (FTY720) Attenuates Myocardial Fibrosis in Post-heterotopic Heart Transplantation

Background and Objective: Sphingosine 1-phosphate (S1P), and S1P receptor modulator fingolimod have been suggested to play important cardioprotective role in animal models of myocardial ischemia/reperfusion injuries. To understand the cardioprotective function of S1P and its mechanism in vivo, we analyzed apoptotic, inflammatory biomarkers, and myocardial fibrosis in an in vivo heterotopic rat heart transplantation model. Methods: Heterotopic heart transplantation is performed in 60 Sprague–Dawley (SD) rats (350–400 g). The heart transplant recipients (n = 60) are categorized into Group A (control) and Group B (fingolimod treated 1 mg/kg intravenous). At baseline with 24 h after heart transplantation, blood and myocardial tissue are collected for analysis of myocardial biomarkers, apoptosis, inflammatory markers, oxidative stress, and phosphorylation of Akt/Erk/STAT-3 signaling pathways. Myocardial fibrosis was investigated using Masson’s trichrome staining and L-hydroxyline. Results: Fingolimod treatment activates both Reperfusion Injury Salvage Kinase (RISK) and Survivor Activating Factor Enhancement (SAFE) pathways as evident from activation of anti-apoptotic and anti-inflammatory pathways. Fingolimod treatment caused a reduction in myocardial oxidative stress and hence cardiomyocyte apoptosis resulting in a decrease in myocardial reperfusion injury. Moreover, a significant (p < 0.001) reduction in collagen staining and hydroxyproline content was observed in fingolimod treated animals 30 days after transplantation demonstrating a reduction in cardiac fibrosis. Conclusion: S1P receptor activation with fingolimod activates anti-apoptotic and anti-inflammatory pathways, leading to improved myocardial salvage causing a reduction in cardiac fibrosis.

Equation-Method for correcting clipping errors in OFDM signals

Orthogonal frequency division multiplexing (OFDM) is the digital modulation technique used by 4G and many other wireless communication systems. OFDM signals have significant amplitude fluctuations resulting in high peak to average power ratios which can make an OFDM transmitter susceptible to non-linear distortion produced by its high power amplifiers (HPA). A simple and popular solution to this problem is to clip the peaks before an OFDM signal is applied to the HPA but this causes in-band distortion and introduces bit-errors at the receiver. In this paper we discuss a novel technique, which we call the Equation-Method, for correcting these errors. The Equation-Method uses the Fast Fourier Transform to create a set of simultaneous equations which, when solved, return the amplitudes of the peaks before they were clipped. We show analytically and through simulations that this method can, correct all clipping errors over a wide range of clipping thresholds. We show that numerical instability can be avoided and new techniques are needed to enable the receiver to differentiate between correctly and incorrectly received frequency-domain constellation symbols.

Digital watermarking using Hall property image decomposition method

AbstractMost of the existing singular value decomposition-based digital watermarking methods are not robust to geometric rotation, which change the pixels’ locations without maintaining the corresponding changes to the pixel’s intensity values of entire image and yield high computational cost. To answer this, we propose a digital image watermarking algorithm using the Hall property. In the proposed method, a digital watermark image is factorized into lower-triangular, upper-triangular, and permutation matrices. The permutation matrix is used as the valid key matrix for authentication of the rightful ownership of the watermark image. The product of the lower and upper triangular matrices is processed with a few iterations of the Arnold transformation to obtain the scrambled data. The scrambled data are embedded into particular sub-bands of a cover image using Wavelet transform. Our experiments show that the proposed algorithm is highly reliable and computationally efficient compared with state-of-the-art methods that are based on singular value decomposition.

An implementation of optimized framework for action classification using multilayers neural network on selected fused features

AbstractIn video sequences, human action recognition is a challenging problem due to motion variation, in frame person difference, and setting of video recording in the field of computer vision. Since last few years, applications of human activity recognition have increased significantly. In the literature, many techniques are implemented for human action recognition, but still they face problem in contrast of foreground region, segmentation, feature extraction, and feature selection. This article contributes a novel human action recognition method by embedding the proposed frames fusion working on the principle of pixels similarity. An improved hybrid feature extraction increases the recognition rate and allows efficient classification in the complex environment. The design consists of four phases, (a) enhancement of video frames (b) threshold-based background subtraction and construction of saliency map (c) feature extraction and selection (d) neural network (NN) for human action classification. Results have been tested using five benchmark datasets including Weizmann, KTH, UIUC, Muhavi, and WVU and obtaining recognition rate 97.2, 99.8, 99.4, 99.9, and 99.9%, respectively. Contingency table and graphical curves support our claims. Comparison with existent techniques identifies the recognition rate and trueness of our proposed method.

Image de-noising with subband replacement and fusion process using bayes estimators, ☆ ☆☆

Abstract A hybrid image de-noising framework with an automatic parameter selection scheme is proposed to handle substantially high noise with an unknown variance. The impetus of the framework is to preserve the latent detail information of the noisy image while removing the noise with an appropriate smoothing and feasible sharpening. The proposed method is executed in two steps. First, the sub-band replacement and fusion process based on accelerated version of the Bayesian non local means method are implemented to enhance the weak edges that often result in low gradient magnitude and fade out during the de-noising process. Then, a truncated beta-Bernoulli process is employed to infer an appropriate dictionary of the edge enhanced data to obtain de-noising results precisely. Numerical simulations are performed to substantiate the restoration of the weak edges through sub-band replacement and fusion process. The proposed de-noising scheme is validated through visual and quantitative results using well established metrics.