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jih-3088
Secured Mechanism Towards Integrity of Digital Images Using DWT, DCT, LSB and Watermarking Integrations
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"Watermarking" is one method in which digital information is buried in a carrier signal;
the hidden information should be related to the carrier signal. There are many different types of
digital watermarking, including traditional watermarking that uses visible media (such as snaps,
images, or video), and a signal may be carrying many watermarks. Any signal that can tolerate
noise, such as audio, video, or picture data, can have a digital watermark implanted in it. A digital
watermark must be able to withstand changes that can be made to the carrier signal in order to
protect copyright information in media files. The goal of digital watermarking is to ensure the
integrity of data, whereas steganography focuses on making information undetectable to humans.
Watermarking doesn't alter the original digital image, unlike public-key encryption, but rather
creates a new one with embedded secured aspects for integrity. There are no residual effects of
encryption on decrypted documents. This work focuses on strong digital image watermarking
algorithms for copyright protection purposes. Watermarks of various sorts and uses were
discussed, as well as a review of current watermarking techniques and assaults. The project shows
how to watermark an image in the frequency domain using DCT and DWT, as well as in the spatial
domain using the LSB approach. When it comes to noise and compression, frequency-domain
approaches are far more resilient than LSB. All of these scenarios necessitate the use of the original
picture to remove the watermark. Out of the three, the DWT approach has provided the best results.
We can improve the resilience of our watermark while having little to no extra influence on image
quality by embedding watermarks in these places. 

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Publication Date
Tue Feb 14 2023
Journal Name
Journal Of Educational And Psychological Researches
University Students' Attitudes towards Reading and Its Relationship to Some Demographic Variables in the Sultanate of Oman
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Abstract

The current study aims to identify university students' attitudes towards reading and its relationship to some demographic variables in the universities of the Sultanate of Oman. The study sample consisted of (1434) male and female university students from various Omani public and private universities affiliated with the Ministry of Higher Education. The study covered all (11) governorates of Oman. The researcher adopted the descriptive analytical approach. The researcher employed a scale of reading attitudes to collect the needed data. The study results showed that university students' reading attitudes recorded a high degree. The results also showed there are statistically significant differences at th

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Publication Date
Wed Mar 16 2022
Journal Name
Journal Of Educational And Psychological Researches
Mental motivation among students of Arabic language departments and its relationship to their attitudes towards the profession
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The aim of the research is to know the level of mental motivation among students of the Arabic language departments in the Faculties of Education in the universities of Baghdad Governorate and its relationship to their attitudes towards the profession, and the level of orientation towards the profession among students of the Arabic language departments in the Faculties of Education. And the correlational relationship between mental motivation and career orientation among students of Arabic language departments in the Faculties of Education, and the current research is determined by students of Arabic language departments in the Faculties of Education and the universities (Education Ibn Rushd-  University of Baghdad, Education- &nbsp

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Publication Date
Mon Nov 01 2021
Journal Name
Journal Of Multidisciplinary Healthcare
Development and Initial Validation of Stigma Towards Healthcare Providers Working with COVID-19 Patients Scale (S19-HCPs)
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Publication Date
Fri Mar 20 2009
Journal Name
Ijcsns International Journal Of Computer Science And Network Security
Pre-processing Importance for Extracting Contours from Noisy Echocardiographic Images
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Contours extraction from two dimensional echocardiographic images has been a challenge in digital image processing. This is essentially due to the heavy noise, poor quality of these images and some artifacts like papillary muscles, intra-cavity structures as chordate, and valves that can interfere with the endocardial border tracking. In this paper, we will present a technique to extract the contours of heart boundaries from a sequence of echocardiographic images, where it started with pre-processing to reduce noise and produce better image quality. By pre-processing the images, the unclear edges are avoided, and we can get an accurate detection of both heart boundary and movement of heart valves.

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Publication Date
Tue Nov 30 2021
Journal Name
Iraqi Journal Of Science
Header-Words Based for Printed Arabic Document Images Retrieval System
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Printed Arabic document image retrieval is a very important and needed system for many companies, governments and various users. In this paper, a printed Arabic document images retrieval system based on spotting the header words of official Arabic documents is proposed. The proposed system uses an efficient segmentation, preprocessing methods and an accurate proposed feature extraction method in order to prepare the document for classification process. Besides that, Support Vector Machine (SVM) is used for classification. The experiments show the system achieved best results of accuracy that is 96.8% by using polynomial kernel of SVM classifier.

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Engineering
Satellite Images Classification in Rural Areas Based on Fractal Dimension
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Fractal geometry is receiving increase attention as a quantitative and qualitative model for natural phenomena description, which can establish an active classification technique when applied on satellite images. In this paper, a satellite image is used which was taken by Quick Bird that contains different visible classes. After pre-processing, this image passes through two stages: segmentation and classification. The segmentation carried out by hybrid two methods used to produce effective results; the two methods are Quadtree method that operated inside Horizontal-Vertical method. The hybrid method is segmented the image into two rectangular blocks, either horizontally or vertically depending on spectral uniformity crit

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Publication Date
Thu Dec 03 2015
Journal Name
Iraqi Journal Of Science
New multispectral images classification method based on MSR and Skewness implementing on various sensor scenes
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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
New multispectral images classification method based on MSR and Skewness implementing on various sensor scenes
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A new features extraction approach is presented based on mathematical form the modify soil ratio (MSR) and skewness for numerous environmental studies. This approach is involved the investigate on the separation of features using frequency band combination by ratio to estimate the quantity of these features, and it is exhibited a particular aspect to determine the shape of features according to the position of brightness values in a digital scenes, especially when the utilizing the skewness. In this research, the marginal probability density function G(MSR) derivation for the MSR index is corrected, that mentioned in several sources including the source (Aim et al.). This index can be used on original input features space for three diffe

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Publication Date
Thu Jul 28 2016
Journal Name
Computer And Information Science
Refinement for Ocular Ultrasound Images Quality by Utilizing Combination of Enhancement Techniques
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Ultrasound has been used as a diagnostic modality for many intraocular diseases, due its safety, low cost, real time and wide availability. Unfortunately, ultrasound images suffer from speckle artifact that are tissue dependent. In this work, we will offer a method to reduce speckle noise and improve ultrasound image to raise the human diagnostic performance. This method combined undecimated wavelet transform with a wavelet coefficient mapping function: where UDWT used to eliminate the noise and a wavelet coefficient mapping function used to enhance the contrast of denoised images obtained from the first component. This methods can be used not only as a means for improving visual quality of medical images but also as a preprocessing

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Advance Science And Technology
MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

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