Preferred Language
Articles
/
ijs-9324
Texture Features Analysis using Gray Level Co-occurrence Matrix for Abnormality Detection in Chest CT Images

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 values for normal tissue.

View Publication Preview PDF
Quick Preview PDF
Publication Date
Wed Dec 26 2018
Journal Name
Iraqi Journal Of Science
Extraction of Vacant Lands for Baghdad City Using Two Classification Methods of Very High Resolution Satellite Images

The use of remote sensing technologies was gained more attention due to an increasing need to collect data for the environmental changes. Satellite image classification is a relatively recent type of remote sensing uses satellite imagery to indicate many key environment characteristics. This study aims at classifying and extracting vacant lands from high resolution satellite images of Baghdad city by supervised Classification tool in ENVI 5.3 program. The classification accuracy was 15%, which can be regarded as fairly acceptable given the difficulty of differentiating vacant land surfaces from other surfaces such as roof tops of buildings.

View Publication Preview PDF
Publication Date
Wed Jul 01 2015
Journal Name
Magnetic Resonance Imaging
Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images

Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images

Scopus (28)
Crossref (23)
Scopus Clarivate Crossref
View Publication
Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
A Review for Arabic Sentiment Analysis Using Deep Learning

     Sentiment Analysis is a research field that studies human opinion, sentiment, evaluation, and emotions towards entities such as products, services, organizations, events, topics, and their attributes. It is also a task of natural language processing. However, sentiment analysis research has mainly been carried out for the English language. Although the Arabic language is one of the most used languages on the Internet, only a few studies have focused on Arabic language sentiment analysis.

     In this paper, a review of the most important research works in the field of Arabic text sentiment analysis using deep learning algorithms is presented. This review illustrates the main steps used in these studies, which include

... Show More
Scopus Crossref
View Publication Preview PDF
Publication Date
Fri Aug 23 2013
Journal Name
International Journal Of Computer Applications
Lossless Compression of Medical Images using Multiresolution Polynomial Approximation Model

In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.

Crossref (4)
Crossref
View Publication
Publication Date
Sun Apr 29 2018
Journal Name
Iraqi Journal Of Science
Intelligent Age Estimation From Facial Images Using Machine Learning Techniques

     Lately, a growing interest has been emerging in age estimation from face images because of the wide range of potential implementations in law enforcement, security control, and human computer interactions. Nevertheless, in spite of the advances in age estimation, it is still a challenging issue. This is due to the fact that face aging process is not only set by distinct elements, such as genetic factors, but by extrinsic factors, such as lifestyle, expressions, and environment as well. This paper applied machine learning technique to intelligent age estimation from facial images using J48 classifier on FG_NET dataset. The proposed work consists of three phases; the first phase is image preprocessing which include

... Show More
View Publication Preview PDF
Publication Date
Fri Jan 01 2016
Journal Name
Diabetic Foot & Ankle
Scopus (13)
Crossref (8)
Scopus Crossref
View Publication
Publication Date
Fri Jan 01 2016
Journal Name
Diabetic Foot & Ankle
Risk factors for occurrence and recurrence of diabetic foot ulcers among Iraqi diabetic patients

There are a few studies that discuss the medical causes for diabetic foot (DF) ulcerations in Iraq, one of them in Wasit province. The aim of our study was to analyze the medical, therapeutic, and patient risk factors for developing DF ulcerations among diabetic patients in Baghdad, Iraq.

Scopus (13)
Crossref (8)
Scopus Crossref
Preview PDF
Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
Scopus (23)
Crossref (20)
Scopus Clarivate Crossref
View Publication
Publication Date
Mon Dec 06 2021
Journal Name
Iraqi Journal Of Science
A Proposed Background Modeling Algorithm for Moving Object Detection Using Statistical Measures

Extracting moving object from video sequence is one of the most important steps
in the video-based analysis. Background subtraction is the most commonly used
moving object detection methods in video, in which the extracted object will be
feed to a higher-level process ( i.e. object localization, object tracking ).
The main requirement of background subtraction method is to construct a
stationary background model and then to compare every new coming frame with it
in order to detect the moving object.
Relied on the supposition that the background occurs with the higher appearance
frequency, a proposed background reconstruction algorithm has been presented
based on pixel intensity classification ( PIC ) approach.

... Show More
View Publication Preview PDF
Publication Date
Wed Jul 24 2024
Journal Name
Journal Of Plant Protection Research
Developing smart sprayer for weed control using an object detection algorithm (yolov5)

Spraying pesticides is one of the most common procedures that is conducted to control pests. However, excessive use of these chemicals inversely affects the surrounding environments including the soil, plants, animals, and the operator itself. Therefore, researchers have been encouraged to...

View Publication