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Machine Learning Approach for Facial Image Detection System
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     Face detection systems are based on the assumption that each individual has a unique face structure and that computerized face matching is possible using facial symmetry. Face recognition technology has been employed for security purposes in many organizations and businesses throughout the world. This research examines the classifications in machine learning approaches using feature extraction for the facial image detection system. Due to its high level of accuracy and speed, the Viola-Jones method is utilized for facial detection using the MUCT database. The LDA feature extraction method is applied as an input to three algorithms of machine learning approaches, which are the J48, OneR, and JRip classifiers.  The experiment’s result indicates that the J48 classifier with LDA achieves the highest performance with 96.0001% accuracy.

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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
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
Thu May 28 2020
Journal Name
Iraqi Journal Of Science
Human Action Recognition Based on Bag-of-Words
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Human action recognition has gained popularity because of its wide applicability, such as in patient monitoring systems, surveillance systems, and a wide diversity of systems that contain interactions between people and electrical devices, including human computer interfaces. The proposed method includes sequential stages of object segmentation, feature extraction, action detection and then action recognition. Effective results of human actions using different features of unconstrained videos was a challenging task due to camera motion, cluttered background, occlusions, complexity of human movements, and variety of same actions performed by distinct subjects. Thus, the proposed method overcomes such problems by using the fusion of featur

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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
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
Fri Mar 27 2020
Journal Name
Iraqi Journal Of Science
Comparison between Dipole-dipole and Pole-dipole Arrays in Delineation of Subsurface Weak Zones Using 2D Electrical Imaging Technique in Al- Anbar University, Western Iraq
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The presence of natural voids and fractures (weak zones) in subsurface gypsiferous soil and gypsum, within the University of Al-Anbar, western Iraq. It causes a harsher problem for civil engineering projects. Electrical resistivity technique is applied as an economic decipher for investigation underground weak zones. The inverse models of the Dipole-dipole and Pole-dipole arrays with aspacing of 2 m and an n-factor of 6 clearly show that the resistivity contrast between the anomalous part of the weak zone and the background. The maximum thickness and shape are well defined from 2D imaging with Dipole-dipole array, the maximum thickness ranges between 9.5 to 11.5 m. It is concluded that the 2D imaging survey is a useful technique and more

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Publication Date
Sun Jan 01 2023
Journal Name
The Egyptian Journal Of Hospital Medicine
The Antimicrobial Activity of Melanin-Mediated Synthesis of Silver Nanoparticles
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Background: Nowadays, the environmentally friendly procedures must be developed to avoid using harmful compounds in synthesis methods. Their increase interest in creating and researching silver nanoparticles (AgNPs) because of their numerous applications in many fields especially medical fields such as burn, wound healing, dental and bone implants, antibacterial, viral, fungal, and arthropodal activities. Biosynthesis of nanoparticles mediated pigments have been widely used as antimicrobial agent against microorganisms. Silver nanoparticles had synthesized by using melanin from locally isolate Pseudomonas aeruginosa, and used as antimicrobial activity against pathogenic microorganisms. Aim of the study: Isolation of Pseudomonas aeruginosa

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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Building a Statistical Model to Detect Foreground Objects and using it in Video Steganography
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Video steganography has become a popular option for protecting secret data from hacking attempts and common attacks on the internet. However, when the whole video frame(s) are used to embed secret data, this may lead to visual distortion. This work is an attempt to hide sensitive secret image inside the moving objects in a video based on separating the object from the background of the frame, selecting and arranging them according to object's size for embedding secret image. The XOR technique is used with reverse bits between the secret image bits and the detected moving object bits for embedding. The proposed method provides more security and imperceptibility as the moving objects are used for embedding, so it is difficult to notice the

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Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Signature Verification Based on Moments Technique
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In this research we will present the signature as a key to the biometric authentication technique. I shall use moment invariants as a tool to make a decision about any signature which is belonging to the certain person or not. Eighteen voluntaries give 108 signatures as a sample to test the proposed system, six samples belong to each person were taken. Moment invariants are used to build a feature vector stored in this system. Euclidean distance measure used to compute the distance between the specific signatures of persons saved in this system and with new sample acquired to same persons for making decision about the new signature. Each signature is acquired by scanner in jpg format with 300DPI. Matlab used to implement this system.

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