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A Review Study on Forgery and Tamper Detection Techniques in Digital Images
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Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of various methodologies in the field was created. Unlike previous studies that focused on picture splicing or copy-move detection, this study intends to investigate the universal type-independent strategies required to identify image tampering. The work provided analyses and evaluates several universal techniques based on resampling, compression, and inconsistency-based detection. Journals and datasets are two examples of resources beneficial to the academic community. Finally, a future reinforcement learning model is proposed.

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Publication Date
Tue Jan 01 2013
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Boundary & Geometric Region Features Image Segmentation for Quadtree Partitioning Scheme
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In this paper, an efficient image segmentation scheme is proposed of boundary based & geometric region features as an alternative way of utilizing statistical base only. The test results vary according to partitioning control parameters values and image details or characteristics, with preserving the segmented image edges.

Publication Date
Tue Jan 18 2022
Journal Name
Iraqi Journal Of Science
Contrast Enhancement of the Mammographic Image Using Retinex with CLAHE methods
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Recently digital mammography is most widely used technology for early detection of breast cancer. The main diagnosing elements such as lesion or masses in digital mammograms are with law contrast. The purpose of this paper is to enhance the mammogram images by increasing its contrast. Different enhancement method are used for this purpose such as histogram equalization (HE), Contrast Limited Adaptive Histogram Equalization (CLAHE), Morphological, and Retinex. The Retinex method also implement by combining it with HE once, and with CLAHE to improve its performance. The experimental results show that using Retinex with CLAHE can produce an image with enhancement in contrast better than using it with HE method and better than other methods

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Publication Date
Wed Feb 16 2022
Journal Name
Iraqi Journal Of Science
Bit-Plane Slicing Autoregressive Modeling for Medical Image Compression
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In this paper, a simple medical image compression technique is proposed, that based on utilizing the residual of autoregressive model (AR) along with bit-plane slicing (BPS) to exploit the spatial redundancy efficiently. The results showed that the compression performance of the proposed techniques is improved about twice on average compared to the traditional autoregressive, along with preserving the image quality due to considering the significant layers only of high image contribution effects.

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Publication Date
Tue Apr 02 2024
Journal Name
Al-iraqia Journal Of Scientific Engineering Research
Prioritise Five Tafseer Translators Using Clustering Technique for Surah Al-Baqarah
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Publication Date
Wed Oct 28 2020
Journal Name
Iraqi Journal Of Science
Robust Blind Watermarking Technique Against Geometric Attacks for Fingerprint Image Using DTCWT-DCT
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In this research paper, a new blind and robust fingerprint image watermarking scheme based on a combination of dual-tree complex wavelet transform (DTCWT) and discrete cosine transform (DCT) domains is demonstrated. The major concern is to afford a solution in reducing the consequence of geometric attacks. It is due to the fingerprint features that may be impacted by the incorporated watermark, fingerprint rotations, and displacements that result in multiple feature sets. To integrate the bits of the watermark sequence into a differential process, two DCT-transformed sub-vectors are implemented. The initial sub-vectors were obtained by sub-sampling in the host fingerprint image of both real and imaginary parts of the DTCWT wavelet coeffi

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Image Steganography by Using Multiwavelet Transform
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Steganography is the art of secret communication. Its purpose is to hide the presence of information, using, for example, images as covers. The frequency domain is well suited for embedding in image, since hiding in this frequency domain coefficients is robust to many attacks. This paper proposed hiding a secret image of size equal to quarter of the cover one. Set Partitioning in Hierarchal Trees (SPIHT) codec is used to code the secret image to achieve security. The proposed method applies Discrete Multiwavelet Transform (DMWT) for cover image. The coded bit stream of the secret image is embedded in the high frequency subbands of the transformed cover one. A scaling factors ? and ? in frequency domain control the quality of the stego

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Publication Date
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
Motion Recording for Surveillance Camera
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In this paper we present an operational computer vision system for real-time motion detection and recording that can be used in surveillance system. The system captures a video of a scene and identifies the frames that contains motion and record them in such a way that only the frames that is important to us is recorded and a report is made in the form of a movie is made and can be displayed. All parts that are captured by the camera are recorded to compare both movies. This serves as both a proof-of- concept and a verification of other existing algorithms for motion detection. Motion frames are detected using frame differencing. The results of the experiments with the system indicate the ability to minimize some of the problems false detec

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
New Approach of Generating Ground-Truth for Local Surveillance Dataset Tested with Benchmark Background Subtraction Models
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     Background subtraction is the dominant approach in the domain of moving object detection. Lots of research has been done to design or improve background subtraction models. However, there are a few well-known and state-of-the-art models that can be applied as a benchmark. Generally, these models are applied to different dataset benchmarks. Most of the time, choosing an appropriate dataset is challenging due to the lack of dataset availability and the tedious process of creating ground-truth frames for the sake of quantitative evaluation. Therefore, in this article, we collected local video scenes of a street and river taken by a stationary camera, focusing on dynamic background challenges. We presented a new technique for creati

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Approximate Analytical Solutions of Bright Optical Soliton for Nonlinear Schrödinger Equation of Power Law Nonlinearity
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This paper introduces the Multistep Modified Reduced Differential Transform Method (MMRDTM). It is applied to approximate the solution for Nonlinear Schrodinger Equations (NLSEs) of power law nonlinearity. The proposed method has some advantages. An analytical approximation can be generated in a fast converging series by applying the proposed approach. On top of that, the number of computed terms is also significantly reduced. Compared to the RDTM, the nonlinear term in this method is replaced by related Adomian polynomials prior to the implementation of a multistep approach. As a consequence, only a smaller number of NLSE computed terms are required in the attained approximation. Moreover, the approximation also converges rapidly over a

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Science
Automatic Number Extraction from Fixed Imaging Distance
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     Developed countries are facing many challenges to convert large areas of existing services to electronic modes, reflecting the current nature of workflow and the equipment utilized for achieving such services. For instance, electricity bill collection still tend to be based on traditional approaches (paper-based and relying on human interaction) making them comparatively time-consuming and prone to human error.

This research aims to recognize numbers in mechanical electricity meters and convert them to digital figures utilizing Optical Character Recognition (OCR) in Matlab. The research utilized the location of red region in color electricity meters image to determine the crop region that contain the meters numbers, then

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