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Linear Feedback Shift Registers-Based Randomization for Image Steganography
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     Steganography involves concealing information by embedding data within cover media and it can be categorized into two main domains: spatial and frequency. This paper presents two distinct methods. The first is operating in the spatial domain which utilizes the least significant bits (LSBs) to conceal a secret message. The second method is the functioning in the frequency domain which hides the secret message within the LSBs of the middle-frequency band of the discrete cosine transform (DCT) coefficients. These methods enhance obfuscation by utilizing two layers of randomness: random pixel embedding and random bit embedding within each pixel. Unlike other available methods that embed data in sequential order with a fixed amount. These methods embed the data in a random location with a random amount, further enhancing the level of obfuscation. A pseudo-random binary key that is generated through a nonlinear combination of eight Linear Feedback Shift Registers (LFSRs) controls this randomness. The experimentation involves various 512x512 cover images. The first method achieves an average PSNR of 43.5292 with a payload capacity of up to 16% of the cover image. In contrast, the second method yields an average PSNR of 38.4092 with a payload capacity of up to 8%. The performance analysis demonstrates that the LSB-based method can conceal more data with less visibility, however, it is vulnerable to simple image manipulation. On the other hand, the DCT-based method offers lower capacity with increased visibility, but it is more robust.

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
The Simulation of Old Human Remains Detecting Utilizing Ground Penetrating Radar Image Processing
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     Many Iraqi provinces had collective cemeteries, especially in the middle and southern regions of Iraq, but many of those cemetery locations are undefined yet. Ground penetration radar has two features that make it optimal from a geophysical perspective for shallowly detecting sensitive materials near the surface. First, the instantaneous image is formed upon scanning, called a radargram. Second, the non-destructive inference of the scanned materials. For these two reasons, this technique was chosen to conduct a simulation process to reveal the old human remains in Iraq's central and southern areas using another model with the same physical feature (old burial) at the AL-Khamisiya site, Thi-Qar province.

The demanded stage

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Publication Date
Mon Aug 30 2021
Journal Name
Al-kindy College Medical Journal
Psychological and Physical Correlates of Body Image Dissatisfaction among High School Egyptian Students
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Background: Body image is one of the most important psychological factors that affects adolescents’ personality and behavior. Body image can be defined as the person’s perceptions, thoughts, and feelings about his or her body.

Objectives: to identify the prevalence of body image concerns among secondary school students and its relation to different factors.

Subjects and methods: A cross-sectional study conducted in which 796 secondary school students participated and body shape concerns was investigated using the body shape questionnaire (BSQ-34).

Results: The prevalence of moderate/marked concern was (21.6%). Moderate/ marked body shape concern was significantly associated

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Publication Date
Wed Aug 16 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Effect of the Number of Gaussian Points and Their Distribution on Image Quality
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This  research  involves  studying  the  influence  of  increasing  the

number of Gaussian points and the style of their distribution, on a circular exit pupil, on the numerical calculations accuracy of the point spread function for an ideal optical system and another system having focus error of (0.25 A. and 0.5 A. )

It was shown that the accuracy of the results depends on the type of

distributing points on the exit pupil. Also, the accuracy increases with the increase of the number of points (N) and the increase of aberrations which requires on increas (N).

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Publication Date
Sun Mar 15 2020
Journal Name
Al-academy
Aesthetics of Hybrid Digital Image Technologies in TV Drama: محمد ثائر عدنان البياتي
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      TV medium derives its formal shape from the technological development taking place in all scientific fields, which are creatively fused in the image of the television, which consists mainly of various visual levels and formations. But by the new decade of the second millennium, the television medium and mainly (drama) became looking for that paradigm shift in the aesthetic formal innovative fields and the advanced expressive performative fields that enable it to develop in treating what was impossible to visualize previously. In the meantime, presenting what is new and innovative in the field of unprecedented and even the familiar objective and intellectual treatments. Thus the TV medium has sought for work

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Publication Date
Wed May 31 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Retrieving Image from Noisy Version depending on Multiwavelet Soft-Thresholding with Smoothing Filter
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In this paper, we describe a new method for image denoising. We analyze properties of the Multiwavelet coefficients of natural images. Also it suggests a method for computing the Multiwavelet transform using the 1st order approximation. This paper describes a simple and effective model for noise removal through suggesting a new technique for retrieving the image by allowing us to estimate it from the noisy image. The proposed algorithm depends on mixing both soft-thresholds with Mean filter and applying concurrently on noisy image by dividing into blocks of equal size (for concurrent processed to increase the performance of the enhancement process and to decease the time that is needed for implementation by applying the proposed algorith

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Publication Date
Sun Dec 09 2018
Journal Name
Journal Of Education In Black Sea Region
Discriminatory and Racist Discourse in American TV Channels: The Image of Arab Immigrants
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The present study examines critically the discursive representation of Arab immigrants in selected American news channels. To achieve the aim of this study, twenty news subtitles have been exacted from ABC and NBC channels. The selected news subtitles have been analyzed within van Dijk’s (2000) critical discourse analysis framework. Ten discourse categories have been examined to uncover the image of Arab immigrants in the American news channels. The image of Arab immigrants has been examined in terms of five ideological assumptions including "us vs. them", "ingroup vs. outgroup", "victims vs. agents", "positive self-presentation vs. negative other-presentation", and "threat vs. non-threat". Analysis of data reveals that Arab immig

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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
A General Overview on the Categories of Image Features Extraction Techniques: A Survey
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In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.

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Publication Date
Mon Mar 20 2023
Journal Name
2023 International Conference On Information Technology, Applied Mathematics And Statistics (icitams)
Hybrid Color Image Compression Using Signals Decomposition with Lossy and Lossless Coding Schemes
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Publication Date
Sun Jun 01 2014
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Medical Image Compression using Wavelet Quadrants of Polynomial Prediction Coding & Bit Plane Slicing
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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

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