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AN ENHANCED METHOD FOR SPRITE EXTRACTING
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The extracting of personal sprite from the whole image faced many problems in separating the sprite edge from the unneeded parts, some image software try to automate this process, but usually they couldn't find the edge or have false result. In this paper, the authors have made an enhancement on the use of Canny edge detection to locate the sprite from the whole image by adding some enhancement steps by using MATLAB. Moreover, remove all the non-relevant information from the image by selecting only the sprite and place it in a transparent background. The results of comparing the Canny edge detection with the proposed method shows improvement in the edge detection.

Publication Date
Mon Jan 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
ON-Line MRI Image Selection and Tumor Classification using Artificial Neural Network
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When soft tissue planning is important, usually, the Magnetic Resonance Imaging (MRI) is a medical imaging technique of selection. In this work, we show a modern method for automated diagnosis depending on a magnetic resonance images classification of the MRI. The presented technique has two main stages; features extraction and classification. We obtained the features corresponding to MRI images implementing Discrete Wavelet Transformation (DWT), inverse and forward, and textural properties, like rotation invariant texture features based on Gabor filtering, and evaluate the meaning of every

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Publication Date
Mon Apr 24 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Quantification of Acrylamide Content in Potato Chips and in Iraqi “Harissa”
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A simple, environmentally benign, sustainable, accurate and cost effective green approach has been developed for the determination of Acrylamide (2-propenamide) in different samples of potato chips collected from the Iraqi market during the year 2012 and a traditional Iraqi meal called Harissa. The method entails a straightforward de-fatting practice with n-hexane, extraction with lukewarm water, and cleanup with solid-phase extraction (SPE) cartridges containing the sorbent bed of the mixed mode ion exchangers (SiliaPrep C8/SCX-2/SAX). The final extracts are directly determined by liquid chromatography-Ultra violet (LC-UV) at a wavelength of 205nm for quantification.  The acrylamide content in the examined potato chips were in the

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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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Publication Date
Fri Jan 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Automatic Detection and Recognition of Car Plates Based on Cascade Classifier
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The study consists of video clips of all cars parked in the selected area. The studied camera height is1.5 m, and the video clips are 18video clips. Images are extracted from the video clip to be used for training data for the cascade method. Cascade classification is used to detect license plates after the training step. Viola-jones algorithm was applied to the output of the cascade data for camera height (1.5m). The accuracy was calculated for all data with different weather conditions and local time recoding in two ways. The first used the detection of the car plate based on the video clip, and the accuracy was 100%. The second is using the clipped images stored in the positive file, based on the training file (XML file), where the ac

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Publication Date
Sun Jul 31 2022
Journal Name
Iraqi Journal Of Science
A Prediction of Skin Cancer using Mean-Shift Algorithm with Deep Forest Classifier
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      Skin cancer is the most serious health problems in the globe because of its high occurrence compared to other types of cancer. Melanoma and non-melanoma are the two most common kinds of skin cancer. One of the most difficult problems in medical image processing is the automatic detection of skin cancer. Skin melanoma is classified as either benign or malignant based on the results of this test. Impediment due to artifacts in dermoscopic images impacts the analytic activity and decreases the precision level. In this research work, an automatic technique including segmentation and classification is proposed. Initially, pre-processing technique called DullRazor tool is used for hair removal process and semi-supervised mean-shift

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Publication Date
Mon Jan 10 2022
Journal Name
Iraqi Journal Of Science
Object Tracking and matching in a Video Stream based on SURF and Wavelet Transform
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In computer vision, visual object tracking is a significant task for monitoring
applications. Tracking of object type is a matching trouble. In object tracking, one
main difficulty is to select features and build models which are convenient for
distinguishing and tracing the target. The suggested system for continuous features
descriptor and matching in video has three steps. Firstly, apply wavelet transform on
image using Haar filter. Secondly interest points were detected from wavelet image
using features from accelerated segment test (FAST) corner detection. Thirdly those
points were descripted using Speeded Up Robust Features (SURF). The algorithm
of Speeded Up Robust Features (SURF) has been employed and impl

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Publication Date
Sun Dec 03 2017
Journal Name
Baghdad Science Journal
Network Self-Fault Management Based on Multi-Intelligent Agents and Windows Management Instrumentation (WMI)
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This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

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Publication Date
Wed Apr 02 2014
Journal Name
Journal Of Theoretical And Applied Information Technology
TUMOR BRAIN DETECTION THROUGH MR IMAGES: A REVIEW OF LITERATURE
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Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Using of Different Satellite-Derived Indices to Detect the Spatiotemporal Changes of the Al-Razzaza Lake, Iraq
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          Remote sensing and GIS applications (Geoinformatics tools) involve a wide range of techniques for providing a solution for future water resources management and offer an excellent means to improve knowledge of sustainable planning. Al-Razzaza is the second largest lake in Iraq; it is a common source of fishery fortune and floodwater reservoir in southwestern Iraq. In recent years, the lake faced a noticeable amount of desiccation, which is considered a threat to the biodiversity and wildlife of the lake. The study aimed to detect the Lake's spatiotemporal changes from 1988 to 2018. Multi satellite-derived indices were investigated for the extracting of the lake water body. Results showed that the lake volume decrea

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Publication Date
Sat May 08 2021
Journal Name
Iraqi Journal Of Science
Automated Deception Detection Systems, a Review
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Humans use deception daily since it can significantly affect their life and provide a getaway solution for any undesired situation. Deception is either related to low-stakes (e.g. innocuous) or high-stakes (e.g. with harmful situations). Deception investigation importance has increased, and it became a critical issue over the years with the increase of security levels around the globe. Technology has made remarkable achievements in many human life fields, including deception detection. Automated deception detection systems (DDSs) are widely used in different fields, especially for security purposes. The DDS is comprised of multiple stages, each of which should be built/trained to perform intelligently so that the whole system can give th

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