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jih-2365
Image Steganography Based on Wavelet Transform and Histogram Modification
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      Recently, digital communication has become a critical necessity and so the Internet has become the most used medium and most efficient for digital communication. At the same time, data transmitted through the Internet are becoming more vulnerable. Therefore, the issue of maintaining secrecy of data is very important, especially if the data is personal or confidential. Steganography has provided a reliable method for solving such problems. Steganography is an effective technique in secret communication in digital worlds where data sharing and transfer is increasing through the Internet, emails and other ways. The main challenges of steganography methods are the undetectability and the imperceptibility of confidential data. This paper presents a steganography method in frequency domain. Haar Wavelet Transform is applied for decomposition of gray level cover image into four sub-bands. The secret image is hidden in the high frequency HH sub-band after applying the histogram modification followed by scrambling process. A Histogram modification is adopted, to scale the secret image to normalize its values, that manipulates the secret image from bright image to dark. Thus the secret image becomes invisible so it can be hidden in the high frequency sub-band.  Scrambling the positions can be for rows then columns, which will give strong security of the hiding process. The experimental results demonstrate the proposed method has achieved superior performance in terms of quantifiable measurement (PSNR and correlation) and in terms of visual quality. The proposed method propositions good imperceptible results and good response for against the various image attacks.

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Publication Date
Mon Dec 03 2012
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Effect of Window Size Changing on Satellite Image Segmentation Using 2D Fast Otsu Method
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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
A Mathematical Approach for Computing the Linear Equivalence of a Periodic Key-Stream Sequence Using Fourier Transform
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A mathematical method with a new algorithm with the aid of Matlab language is proposed to compute the linear equivalence (or the recursion length) of the pseudo-random key-stream periodic sequences using Fourier transform. The proposed method enables the computation of the linear equivalence to determine the degree of the complexity of any binary or real periodic sequences produced from linear or nonlinear key-stream generators. The procedure can be used with comparatively greater computational ease and efficiency. The results of this algorithm are compared with Berlekamp-Massey (BM) method and good results are obtained where the results of the Fourier transform are more accurate than those of (BM) method for computing the linear equivalenc

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Publication Date
Thu Jul 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Analytical Solutions to Investigate Fractional Newell-Whitehead Nonlinear Equation Using Sumudu Transform Decomposition Method
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Some nonlinear differential equations with fractional order are evaluated using a novel approach, the Sumudu and Adomian Decomposition Technique (STADM). To get the results of the given model, the Sumudu transformation and iterative technique are employed. The suggested method has an advantage over alternative strategies in that it does not require additional resources or calculations. This approach works well, is easy to use, and yields good results. Besides, the solution graphs are plotted using MATLAB software. Also, the true solution of the fractional Newell-Whitehead equation is shown together with the approximate solutions of STADM. The results showed our approach is a great, reliable, and easy method to deal with specific problems

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Publication Date
Fri Apr 15 2016
Journal Name
International Journal Of Computer Applications
Hybrid Techniques based Speech Recognition
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Information processing has an important application which is speech recognition. In this paper, a two hybrid techniques have been presented. The first one is a 3-level hybrid of Stationary Wavelet Transform (S) and Discrete Wavelet Transform (W) and the second one is a 3-level hybrid of Discrete Wavelet Transform (W) and Multi-wavelet Transforms (M). To choose the best 3-level hybrid in each technique, a comparison according to five factors has been implemented and the best results are WWS, WWW, and MWM. Speech recognition is performed on WWS, WWW, and MWM using Euclidean distance (Ecl) and Dynamic Time Warping (DTW). The match performance is (98%) using DTW in MWM, while in the WWS and WWW are (74%) and (78%) respectively, but when using (

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Publication Date
Wed Sep 11 2024
Journal Name
Lecture Notes In Civil Engineering
An Image Processing Algorithm to Address the Problem of Stains Merge on Water Sensitive Papers and Its Impact on the Evaluation of Spray Quality Indicators
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There are many techniques that can be used to estimate the spray quality traits such as the spray coverage, droplet density, droplet count, and droplet diameter. One of the most common techniques is to use water sensitive papers (WSP) as a spray collector on field conditions and analyzing them using several software. However, possible merger of some droplets could occur after they deposit on WSP, and this could affect the accuracy of the results. In this research, image processing technique was used for better estimation of the spray traits, and to overcome the problem of droplet merger. The droplets were classified as non-merged and merged droplets based on their roundness, then the merged droplets were separated based on the average non-m

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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On Reliability Estimation for the Exponential Distribution Based on Monte Carlo Simulation
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        This Research deals with estimation the reliability function for two-parameters Exponential distribution, using different estimation methods ; Maximum likelihood, Median-First Order Statistics, Ridge Regression, Modified Thompson-Type Shrinkage and Single Stage Shrinkage methods. Comparisons among the estimators were made using Monte Carlo Simulation based on statistical indicter mean squared error (MSE) conclude that the shrinkage method perform better than the other methods

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Publication Date
Wed Feb 10 2016
Journal Name
Scientific Reports
Experimental demonstration on the deterministic quantum key distribution based on entangled photons
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As an important resource, entanglement light source has been used in developing quantum information technologies, such as quantum key distribution(QKD). There are few experiments implementing entanglement-based deterministic QKD protocols since the security of existing protocols may be compromised in lossy channels. In this work, we report on a loss-tolerant deterministic QKD experiment which follows a modified “Ping-Pong”(PP) protocol. The experiment results demonstrate for the first time that a secure deterministic QKD session can be fulfilled in a channel with an optical loss of 9 dB, based on a telecom-band entangled photon source. This exhibits a conceivable prospect of ultilizing entanglement light source in real-life fiber-based

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Publication Date
Fri Feb 04 2022
Journal Name
Neuroquantology
Detecting Damaged Buildings on Post-Hurricane Satellite Imagery based on Transfer Learning
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In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Hiding the Type of Skin Texture in Mice based on Fuzzy Clustering Technique
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A substantial matter to confidential messages' interchange through the internet is transmission of information safely. For example, digital products' consumers and producers are keen for knowing those products are genuine and must be distinguished from worthless products. Encryption's science can be defined as the technique to embed the data in an images file, audio or videos in a style which should be met the safety requirements. Steganography is a portion of data concealment science that aiming to be reached a coveted security scale in the interchange of private not clear commercial and military data. This research offers a novel technique for steganography based on hiding data inside the clusters that resulted from fuzzy clustering. T

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network
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         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

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Scopus (9)
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