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The Use of Contrast and Gradient Features to Categorize Texture Images
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     Image texture is an important part of many types of images, for example medical images. Texture Analysis is the technique that uses measurable features to categorize complex textures. The main goal is to extract discriminative features that are used in different pattern recognition applications and texture categorization. This paper investigates the extraction of most discriminative features for different texture images from the “Colored Brodatz” dataset using two types of image contrast measures, as well as using the statistical moments on five bands (red, green, blue, grey, and black). The Euclidean distance measure is used in the matching step to check the similarity degree. The proposed method was tested on 112 classes of textures. The achieved results showed that the proposed method is accurate and fast concerning classification accuracy with low computational complexity. The achieved Recognition Rate (RR) was 100%.

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Using Fuzzy Clustering to Detect the Tumor Area in Stomach Medical Images
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Although the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t

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Publication Date
Mon Oct 03 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Use of learning methods for gender and age classification based on front shot face images
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Publication Date
Mon Nov 29 2021
Journal Name
Iraqi Journal Of Science
Foreground Object Detection and Separation Based on Region Contrast
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Foreground object detection is one of the major important tasks in the field of computer vision which attempt to discover important objects in still image or image sequences or locate related targets from the scene. Foreground objects detection is very important for several approaches like object recognition, surveillance, image annotation, and image retrieval, etc. In this work, a proposed method has been presented for detection and separation foreground object from image or video in both of moving and stable targets. Comparisons with general foreground detectors such as background subtraction techniques our approach are able to detect important target for case the target is moving or not and can separate foreground object with high det

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Publication Date
Thu Oct 01 2009
Journal Name
Iraqi Journal Of Physics
Gray-Scale Image Brightness/Contrast Enhancement with Multi-Model Histogram linear Contrast Stretching (MMHLCS) method
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Gray-Scale Image Brightness/Contrast Enhancement with Multi-Model
Histogram linear Contrast Stretching (MMHLCS) method

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Publication Date
Sat Jan 20 2024
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Enhanced Support Vector Machine Methods Using Stochastic Gradient Descent and Its Application to Heart Disease Dataset
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Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

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Publication Date
Wed Jun 14 2023
Journal Name
Al-academy
External treatments for the space between the institute and the contrast in contemporary theater
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Theater is a renewed art until this moment, and it does not stray from its components from life and its spaces in general, but rather is derived from them according to characteristics and directions intended to differ based on finding other, more effective solutions, Therefore, the research entitled (Extractive treatments of the space between tradition and contrast in contemporary theater) consists of four chapters. The first chapter came under the title (the methodological framework). Where he dealt with the research problem and then the importance of the research and the goal of the research as well as the objective, temporal and spatial limits of the research, In addition to defining the terminology and then finding the procedural ter

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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
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
the effect of soil texture with limited saltiness concentration
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Found through the study of tissues Alnbarh and domestic focus where a direct impact on the development of the larvae mature into pupae and then to adults appeared to clay soils have a negative impact more than sandy soil at different concentrations salt where as it turns out that the percentage of evolution fly larvae worm Lhalzonnih of the ancient worldadult to have reached more than 80%

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Publication Date
Sun Dec 31 2023
Journal Name
College Of Islamic Sciences
The concept of inconsistency and measuring the inverse relationship between overlap and contrast.
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abstract:

The aim of this study is to clarify the relationship between the concept of  inconsistency and the measurement of the inverse relationship of overlap and contrast. The study will address the following points:

  1. Explaining the true nature of inconsistency and contrast, as understanding their relationship is essential for determining them.
  2. Examining the view of the scholars regarding their significance as approaches to understanding the relationship.
  • Identifying the relationship between inconsistency and contrast in terms of overlap and contrast.

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Publication Date
Sun May 17 2020
Journal Name
Iraqi Journal Of Science
Numerical Solutions for the Optimal Control Governing by Variable Coefficients Nonlinear Hyperbolic Boundary Value Problem Using the Gradient Projection, Gradient and Frank Wolfe Methods
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This paper is concerned with studying the numerical solution for the discrete classical optimal control problem (NSDCOCP) governed by a variable coefficients nonlinear hyperbolic boundary value problem (VCNLHBVP). The DSCOCP is solved by using the Galerkin finite element method (GFEM) for the space variable and implicit finite difference scheme (GFEM-IFDS) for the time variable to get the NS for the discrete weak form (DWF) and for the discrete adjoint weak form (DSAWF) While, the gradient projection method (GRPM), also called the gradient method (GRM), or the Frank Wolfe method (FRM) are used to minimize the discrete cost function (DCF) to find the DSCOC. Within these three methods, the Armijo step option (ARMSO) or the optimal step opt

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