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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 Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Sat Sep 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Image Steganalysis Using Image Quality Metrics (Structural Contents Metric)
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A new method presented in this work to detect the existence of hidden

data as a secret message in images. This method must be applyied only on images which have the same visible properties (similar in perspective) where the human eyes cannot detect the difference between them.

This method is based on Image Quality Metrics (Structural Contents

Metric), which means the comparison between the original images and stego images, and determines the size ofthe hidden data. We applied the method to four different images, we detect by this method the hidden data and  find exactly the same size of the hidden data.

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Publication Date
Fri Apr 01 2016
Journal Name
Al–bahith Al–a'alami
Indicators of Mental image among Students of the University of Baghdad about Iraqi Political Parties-(a research based on a master thesis)
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Media studies have focused mostly on the issue of the mental image because the image that is formed in the mind has become not only a photo of a human being and having kept for himself. This image has an outside influence which may sometimes up to the formation of the fate of others and it sometimes includes individuals and groups together.
This study comes in the context of identifying the image of Iraqi political parties among Iraqi university students and the nature of the view that students have in their minds about these parties.
Chapter one includes the problem of the research, the importance of the study, the goals and method used. Chapter two is divided into two sections: section one deals with the concept of the mental i

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Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
New Adaptive Satellite Image Classification Technique for Al habbinya Region West of Iraq
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   Developing a new adaptive satellite images classification technique, based on a new way of merging between regression line of best fit and new empirical conditions methods. They are supervised methods to recognize different land cover types on Al habbinya region. These methods should be stand on physical ground that represents the reflection of land surface features.      The first method has separated the arid lands and plants. Empirical thresholds of different TM combination bands; TM3, TM4, and TM5 were studied in the second method, to detect and separate water regions (shallow, bottomless, and very bottomless). The Optimum Index Factor (OIF) is computed for these combination bands, which realized

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Publication Date
Tue Jan 30 2018
Journal Name
Iraqi Journal Of Science
Improve the Spatial Resolution of Multispectral satellite Image using Different Image Sharpening Techniques
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The process of combining the significant information from a series of images into a single image called image sharpening or image fusing, where the resultant fused image will be having more spatial and spectral information than any of the input images. in this research two images of the same place in different spatial resolution have been used the first one was panchromatic and the second image was multispectral with spatial resolution 0.5m and 2 m respectively. These images were captured by world view-2 sensor. This research resent four pan sharpening methods like (HSV, Brovey (color normalizes) , Gram shmidt and PCA)these methods were used to combine the adopted images to get multispectral image

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
A Cryptosystem for Database Security Based on TSFS Algorithm
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Implementation of TSFS (Transposition, Substitution, Folding, and Shifting) algorithm as an encryption algorithm in database security had limitations in character set and the number of keys used. The proposed cryptosystem is based on making some enhancements on the phases of TSFS encryption algorithm by computing the determinant of the keys matrices which affects the implementation of the algorithm phases. These changes showed high security to the database against different types of security attacks by achieving both goals of confusion and diffusion.

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Publication Date
Mon Jun 01 2015
Journal Name
. International Journal Of Computer Science And Mobile Computing
A Hybrid Lossy Image Compression based on Wavelet Transform, Polynomial Approximation Model, Bit Plane Slicing and Absolute Moment Block Truncation
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Publication Date
Wed Jan 02 2019
Journal Name
Journal Of The College Of Languages
Функциональная транспозиция причастий в прилагательное Functional Shift of Present and Past Participles from No-minal Meaning to Adjectival Meaning
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Publication Date
Wed Jan 02 2019
Journal Name
Journal Of The College Of Languages (jcl)
Functional Shift of Present and Past Participles from No-minal Meaning to Adjectival Meaning: Функциональная транспозиция причастий в прилагательное
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This paper tackles in detail the functional shift of parts of speech, such as the shift of a verbal clause to an adjectival clause, along with the types of such a shift. The researcher identified the important features of participles, as well as the concept of participles, adjectives, and their types. Also, the most important changes that affect the participles during such shifts. Further, an exposition is made of the different producers through which a verbal clause is changed into an adjectival one in Russian.

      This type of functional shift in parts of speech is seen as a process of deriving most of the new words in contemporary Russian. Russian is very rich in new words, whether by way of processe

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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Finite Element Method With Linear Rectangular Element for Solving Nanoscale InAs⁄GaAs Quantum Ring Structures
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        This paper is concerned with the solution of the nanoscale structures consisting of the   with an effective mass envelope function theory, the electronic states of the  quantum ring are studied.  In calculations, the effects due to the different effective masses of electrons in and out the rings are included. The energy levels of the electron are calculated in the different shapes of rings, i.e., that the inner radius of rings sensitively change the electronic states. The energy levels of the electron are not sensitively dependent on the outer radius for large rings. The structures of  quantum rings are studied by the one electronic band Hamiltonian effective mass approximati

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