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This paper presents a new algorithm on wavelet based robust and invisible digital image watermarking for multimedia security. The proposed algorithm has been designed, implemented and verified using MATLAB R2014a simulation for both embedding and extraction of the watermark and the results of which shows significant improvement in performance metrics like PSNR, SSIM, Mean Correlation, MSE than the...
This paper proposes a new method using fractional autocorrelation and the Haar wavelet transform to estimate the parameters of phase code and linear frequency modulation combined signal. The combined signal is transformed into a linear frequency modulation signal using square method and its chirp rate is estimated by fractional autocorrelation firstly. Then, the initial frequency is estimated through...
Medical image processing is considered as an important topic in the domain of image processing. It is used to help the doctors to improve and speed up the diagnosis process. In particular, computed tomography scanners (CT-Scanner) are used to create cross-sectional medical 3D images of bones. In this paper, we propose a method for CT-Scanner identification based on the sensor noise analysis. We built...
To automatically detect blur in images, without needing to perform blur kernel estimation, we develop a new blur descriptor. It is modeled by image perceptual gradient statistics. As blurring affects especially edges, the proposed idea turns on extract specific statistical features from the perceptual edge map in the wavelet domain using the just noticeable blur concept (JNB). Extracted statistical...
It is a challenging problem to detect and analyze gait signals for health evaluation. In this article, we propose a comprehensive assessment method using multiple time scale features to extract gait signal characteristics. Multi-resolution wavelet transform, together with logic regression and correlation analysis, was adapted for statistical analysis. The results show that the primary period and autocorrelation...
Internet traffic exhibits self-similarity and long-range dependence (LRD). Accurate estimation of statistical parameters characterizing self-similarity and LRD is an important issue, aiming at best modelling traffic e.g. to the purpose of network simulation. Major attention has been devoted to designing algorithms for estimating the Hurst parameter H of LRD traffic series or, more generally, the exponent...
Autism Spectrum Disorder (ASD) is a neural development disorder affecting the information processing capability of the brain by altering how nerve cells and their synapses interconnect and organize. Electroencephalograph or EEG signals records the electrical activity of the brain from the scalp which can be utilized to identify and investigate the brain wave pattern which are specific to individuals...
In neonatal research, physiological signals are often degraded by an artifact generated by movement of the infant. Portions of these movement embedded signals are commonly excluded in the analysis of the relevant physiological signal. However, movement may be a significant marker of physiological development of the infant. Here we present results from a wavelet-based algorithm that quantifies neonatal...
Holter electrocardiogram (ECG) is the recording of the electrical activity of heart in order to assess its functionality during day-to-day activities. This involves a large amount of data to be recorded from multiple recording points of the body for a longer duration. The storage and transmission of this large volume of data is a great challenge. In this work, we propose a new adaptive algorithm for...
Recently, texture-based features have been used for digitized historical document image segmentation. It has been proven that these methods work effectively with no a priori knowledge. Moreover, it has been shown that they are robust when they are applied on degraded documents under different noise levels and types. In this paper an approach of evaluating texture-based feature sets for segmenting...
Land masking is one essential preprocessing technique for ship recognition from synthetic aperture radar (SAR) images. This paper presents a novel land masking procedure based on wavelet transform(WT). Low-pass (L-P) images for several wavelet scales are produced. Two wavelet correlation criteria are developed to fuse useful information at multiple scales. The first criterion makes land segmentation...
Nowadays, content-based image-retrieval techniques constitute powerful tools for archiving and mining of large remote sensing image databases. However, the gap between low-level unsupervised extracted features in content-based retrieval and the high-level semantic concepts of user queries limits their performances. For that reason, we propose an adaptive content based image retrieval (CBIR) approach...
Brain electrical activity is often recorded via electroencephalogram (EEG) since it can be monitored using noninvasive and affordable recording equipment. When it comes to the analysis of EEG, there is a lack of signal processing technique to deal with the nonstationarity and nonlinearity of EEG signals. Here we present the data-driven algorithm, empirical mode decomposition suitable for the analysis...
This work presents a two-phase image registration technique utilizing a hybrid feature-based and an area-based similarity measure of partially overlapped aerial imagery in presence of affine translation and rotation transformations. The resulting selectively guided execution of similarity measures provides a reduction in search space, reducing the computational cost of the proposed algorithm. This...
In this paper, we evaluated and compared the QoS behavior of video traffic models for H.264 AVC video. The H.264 AVC models that we evaluated are: the Markov Modulated Gamma (MMG) model, the Discrete Autoregressive (DAR) model, the second order Autoregressive AR(2) model, and a wavelet-based model. These models were used to generate synthetic packet traces which were used in a simulation model to...
Compressive sampling (CS) aims at acquiring a signal at a sampling rate below the Nyquist rate by exploiting prior knowledge that a signal is sparse or correlated in some domain. Despite the remarkable progress in the theory of CS, the sampling rate on a single image required by CS is still very high in practice. In this paper, a non-local compressive sampling (NLCS) recovery method is proposed to...
In real time biometric based authentication environments, wavelet based functions are widely incorporated as one of the promising methods for feature extraction of biometric traits. In this paper, we propose a novel finger knuckle print (FKP) recognition technique based on Haar-Wavelet Transform (HWT). Haar - Wavelet transform is used to transform the original knuckle image into a subset of its feature...
In an effort to simplify the analysis of data represented by networks, a classical approach is to uncover the community structure of the underlying graph. In this work, we take advantage of graph wavelets and the associated natural definition of scale to propose a multi-scale community mining tool. More precisely, at a given scale, we cluster nodes in the same community when their corresponding wavelets...
Most of the current pitch detection algorithms can not work well under the high noise environment. For this reason, a pitch detection algorithm for noisy speech signals based on wavelet transform and autocorrelation function is proposed. First, the noisy speech signals are decomposed by three-layer wavelet transform in order to get rid of the high frequency noise and obtain the approximate signals...
Standard 12-lead (S12) system and Mason-Likar 12-lead (ML12) system despite of being most acceptable systems for clinical usage are not the preferred lead systems for remote monitoring (RM) applications. Usually RM applications involve wireless transmission of signals and a 2–3 lead system is preferred for bandwidth and storage limitations and data transmission time. Generally, ECG compression techniques...
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