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Comparative analysis of Median filter family for Removing High-Density Noise in Magnetic Resonance Images
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Magnetic Resonance Imaging (MRI) is a medical indicative test utilized for taking images of the tissue points of interest of the human body. During image acquisition, MRI images can be damaged by many noise signals such as impulse noise. One reason for this noise may be a sharp or sudden disturbance in the image signal. The removal of impulse noise is one of the real difficulties. As of late, numerous image de-noising methods were produced for removing the impulse noise from images. Comparative analysis of known and modern methods of median filter family is presented in this paper. These filters can be categorized as follows: Standard Median Filter; Adaptive Median Filter; Progressive Switching Median Filter; Noise Adaptive Fuzzy Switching Median Filter; and Different Applied Median Filter. The de-noising technique performance for each one is evaluated and compared using Peak Signal Noise Ratio, Structural Similarity index Metric, and Beta metric as quantitative metrics.  The experimental results showed that the latest de-noising technique, Different Applied Median Filter (DAMF), produced better results in removing impulse noise compared with the other de-noising techniques. However, this filter produced de-noised image with nonlinear edges in high-density noise. As a result, noise removal from images is one of the low-level images processing which is considered as a first step in many image applications. Therefore, the efficiency of any image processed depends on the efficiency of noise removal technique.

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Publication Date
Sun Jan 01 2017
Journal Name
Journal Of Engineering
Evaluation of Textile Filter in Field Drains
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The role of drain in agricultural lands is to remove excess surface and subsurface water to create a good environment for root growth and to increase crops yield. The main objective of this research was to evaluate the performance of closed drains when using textile filter instead of crushed gravel filter. The research has been executed in the laboratory using a sand tank model and by using two types of the soil. One of soils was light soil (sandy soil) and the other heavy soil (loamy soil). The tests were classified into four cases; each case was supplied discharge during 10 days. The results showed that the amount of out flow when using graded crushed gravel filter is greater than the amount of out flow in case of usin

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Publication Date
Sun Jun 01 2014
Journal Name
University Of Baghdad
New Analytical Methods for Drugs Analysis A Comparative Study
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Four different spectrophotometric methods are used in this study for the determination of Sulfamethoxazole and sulfanilamide drugs in pharmaceutical compounds, synthetic samples, and in their pure forms. The work comprises four chapters which are shown in the following: Chapter One: Includes a brief for Ultraviolet-Visible (UV-VIS) Absorption spectroscopy, antibacterial drugs and sulfonamides with some methods for their determination. The chapter lists two methods for optimization; univariate method and multivariate method. The later includes different types, two of these were mentioned; simplex method and design of experiment method. Chapter Two: Includes reaction of the two studied drugs with sodium nitrite and hydrochloric acid for diazo

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Publication Date
Thu Dec 29 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Technique For Image De-blurring Using Adaptive Wavelet Lagrange Fuzzy Filter
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A new de-blurring technique was proposed in order to reduced or remove the blur in the images. The proposed filter was designed from the Lagrange interpolation calculation with adjusted by fuzzy rules and supported by wavelet decomposing technique. The proposed Wavelet Lagrange Fuzzy filter gives good results for fully and partially blurring region in images.
 

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Publication Date
Sat Dec 31 2016
Journal Name
Al-kindy College Medical Journal
A Comparison of Sagittal Sections of Short T1inversion Recovery and T2 Weighted Fast Spin Echo Magnetic Resonance Sequences for Detection of Multiple Sclerosis Spinal Cord Lesions
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Background: Multiple sclerosis is a chronic autoimmune inflammatory demyelinating disease of the central nervous system of unknown etiology. Different techniques and magnetic resonance image sequences are widely used and compared to each other to improve the detection of multiple sclerosis lesions in the spinal cord. Objective: To evaluate the ability of MRI short tau inversion recovery sequences in improvementof multiple sclerosis spinal cord lesion detection when compared to T2 weighted image sequences. Type of the study: A retrospective study. Methods: this study conducted from 15thAugust 2013 to 30thJune 2014 at Baghdad teaching hospital. 22 clinically definite MS patients with clinical features suggestive of spinal cord involvement,

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Effect of high and low density polyethylene on some mechanical properties of concrete
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The increasing use of plastics in various aspects of modern life resulted in the availability of enormous amount of wastes, including a negative effect on the environment and humans. So it is necessary to find solutions to deal with these wastes and ensure to use them as solutions to use in concrete mix . In this research the production of concrete containing high and low density polyethylene has been used by (5, 10, 15)% as a replacement of part of the volume of sand, so as to obtain concrete good compressive strength as well as other benefits such as improved possibility of pumping concrete and reduce the loss of concrete for workability polymer is a material that is non-absorbable of water . It is also intended to dispose of these was

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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Texture Features Analysis using Gray Level Co-occurrence Matrix for Abnormality Detection in Chest CT Images
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Texture is an important characteristic for the analysis of many types of images because it provides a rich source of information about the image. Also it provides a key to understand basic mechanisms that underlie human visual perception. In this paper four statistical feature of texture (Contrast, Correlation, Homogeneity and Energy) was calculated from gray level Co-occurrence matrix (GLCM) of equal blocks (30×30) from both tumor tissue and normal tissue of three samples of CT-scan image of patients with lung cancer. It was found that the contrast feature is the best to differentiate between textures, while the correlation is not suitable for comparison, the energy and homogeneity features for tumor tissue always greater than its valu

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Publication Date
Fri Sep 30 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Thermal and Catalytic Degradation Kinetics of High-Density Polyethylene Over NaX Nano-Zeolite
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Thermal and catalytic pyrolysis of waste plastics in an inert atmosphere has been regarded as a creative method, since pyrolysis can convert plastics waste into hydrocarbons that can be used either as fuels or as a source of chemicals.

Natural Iraqi kaolin clay was used to synthesis the NaX nano- zeolite by hydrothermal conditions with average particle size equal to 77.63nm.Thermal decomposition kinetics of high-density polyethylene (HDPE) in the absence and presence of catalysts nano NaX Zeolite was investigated. Thermal and catalytic degradation of HDPE was performed using a thermogravimetric analyzer in nitrogen atmosphere under non-isothermal conditions 4, 7 and 10 °C/min heating rates were employed in thermogravimetric anal

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Clouds Height Classification Using Texture Analysis of Meteosat Images
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In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

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Publication Date
Mon Dec 03 2018
Journal Name
Journal Of Engineering
Comparative Analysis of Various Multicarrier Modulation Techniques for Different Multilevel Converters
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The applications of Multilevel Converter (MLC) are increased because of the huge demand for clean power; especially these types of converters are compatible with the renewable energy sources. In addition, these new types of converters have the capability of high voltage and high power operation. A Nine-level converter in three modes of implementation; Diode Clamped-MLC (DC-MLC), Capacitor Clamped-MLC (CC-MLC), and the Modular Structured-MLC (MS-MLC) are analyzed and simulated in this paper. Various types of Multicarrier Modulation Techniques (MMTs) (Level shifted (LS), and Phase shifted (PS)) are used for operating the proposed Nine level - MLCs. Matlab/Simulink environment is used for the simulation, extracting, and ana

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Publication Date
Sun Oct 02 2022
Journal Name
Engineering, Technology & Applied Science Research
Statistical Modeling for Traffic Noise: The Case of Kirkuk City
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The auditory system can suffer from exposure to loud noise and human health can be affected. Traffic noise is a primary contributor to noise pollution. To measure the noise levels, 3 variables were examined at 25 locations. It was found that the main factors that determine the increase in noise level are traffic volume, vehicle speed, and road functional class. The data have been taken during three different periods per day so that they represent and cover the traffic noise of the city during heavy traffic flow conditions. Analysis of traffic noise prediction was conducted using a simple linear regression model to accurately predict the equivalent continuous sound level. The difference between the predicted and the measured noise shows that

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