Taha Rassem

Taha Rassem
Bournemouth University | BU · Faculty of Science and Engineering

PhD in Computer Engineering ( Imaging and computer vision)

About

61
Publications
14,083
Reads
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598
Citations
Introduction
Taha H. Rassem received the B.Sc. degree in Computer Engineering from University of Technology, Baghdad, Iraq in 2001, M.Tech in Computer Science from University of Hyderabad, Hyderabad, India in 2007 and PhD in the School of Electrical & Electronic Engineering (Computer Engineering- Image Processing) from Universiti Sains Malaysia in 2014. He was an assistant lecturer in Computer Engineering Department, School of Computer Science and Engineering at Hodeidah University, Hodeidah, Yemen. Currently, he is a senior lecturer in faculty of computer systems and software engineering, Universiti Malaysia Pahang (UMP). His research interest is in the area of image classification, object recognition, and digital watermarking.
Additional affiliations
March 2015 - present
Universiti Malaysia Pahang
Position
  • Proposal defense coordinator
August 2014 - present
Universiti Malaysia Pahang
Position
  • Senior Lecturer
August 2014 - October 2020
Universiti Malaysia Pahang
Position
  • Senior Lecturer
Description
  • Data Visualization Image Processing Object Oriented Programming (JAVA)
Education
February 2008 - July 2014
Universiti Sains Malaysia
Field of study
  • Computer Engineering - Imaging
July 2005 - September 2007
University of Hyderabad
Field of study
  • Computer Science
September 1997 - September 2001
University of Technology, Iraq
Field of study
  • Computer Engineering

Publications

Publications (61)
Article
Full-text available
Intracranial hemorrhaging is considered a type of disease that affects the brain and is very dangerous, with high-mortality cases if there is no rapid diagnosis and prompt treatment. CT images are one of the most important methods of diagnosing intracranial hemorrhages. CT images contain huge amounts of information, requiring a lot of experience an...
Article
On the Ethereum network, users communicate with one another through a variety of different accounts. Pseudo-anonymity was enforced over the network to provide the highest level of privacy. By using accounts that engage in fraudulent activity across the network, such privacy may be exploited. Like other cryptocurrencies, Ethereum blockchain may expl...
Article
Full-text available
Cancer is considered one of the most aggressive and destructive diseases that shortens the average lives of patients. Misdiagnosed brain tumours lead to false medical intervention, which reduces patients' chance of survival. Accurate early medical diagnoses of brain tumour are an essential point for starting treatment plans that improve the surviva...
Article
Full-text available
Stroke and cerebral haemorrhage are the second leading causes of death in the world after ischaemic heart disease. In this work, a dataset containing medical, physiological and environmental tests for stroke was used to evaluate the efficacy of machine learning, deep learning and a hybrid technique between deep learning and machine learning on the...
Article
Full-text available
Eye tracking is a useful technique for detecting autism spectrum disorder (ASD). One of the most important aspects of good learning is the ability to have atypical visual attention. The eye-tracking technique provides useful information about children’s visual behaviour for early and accurate diagnosis. It works by scanning the paths of the eyes to...
Article
Full-text available
Dementia and Alzheimer’s disease are caused by neurodegeneration and poor communication between neurons in the brain. So far, no effective medications have been discovered for dementia and Alzheimer’s disease. Thus, early diagnosis is necessary to avoid the development of these diseases. In this study, efficient machine learning algorithms were ass...
Article
This paper presents a novel inertia moment estimation algorithm to enable the Active Force Control Scheme for tracking a wheeled mobile robot (WMR) effectively in a specific trajectory within constrained environments such as on roads or in factories. This algorithm, also known as laser simulator logic, has the capability to estimate the inertia mom...
Article
Full-text available
The textual analysis has become the most important task due to the rapid increase of the number of texts that have been continuously generated in several forms such as posts and chats in social media, emails, articles, and news. The management of these texts requires efficient and effective methods, which can handle the linguistic issues that come...
Article
Full-text available
Face recognition is one of the most interesting areas of research areas because of its importance in authentication and security. Differentiating between different facial images is not easy because of the similarities in facial features. Human faces can also be covered obscured by eyeglasses, facial expressions and hairstyles can also be changed ca...
Chapter
Full-text available
Text processing has been playing a great role in information retrieval to solve the problem of ambiguity in natural language processing, e.g., internet search, data mining, and social media. In semantic similarity, it will be used to analyze the relationships between Word-Pairs on social media. Organizing a huge number of unstructured text document...
Article
Full-text available
The accurate diagnosis of Alzheimer’s disease (AD) plays an important role in patient treatment, especially at the disease’s early stages, because risk awareness allows the patients to undergo preventive measures even before the occurrence of irreversible brain damage. Although many recent studies have used computers to diagnose AD, most machine de...
Article
Full-text available
Measuring semantic relatedness has received much attention for uses in many fields such as information retrieval and natural language processing. For handling synonymous problem in distributional-based measures, many researchers are investigating how to exploit semantic features in lexical sources to form knowledge-based measures. In the knowledge-...
Article
Full-text available
LBP is one of the simplest yet most powerful feature extraction descriptors. Many descriptors based on LBP have been proposed to improve its performance. Completed Local Ternary Pattern (CLTP) is one of the important LBP variants that was proposed to overcome LBP’s drawbacks. However, despite the impressive performance of CLTP, it suffers from some...
Conference Paper
Full-text available
The textual analysis has become most important task due to the rapid increase of the number of texts that have been continuously generated in several forms such as posts and chats in social media, emails, articles, and news. The management of these texts requires efficient and effective methods, which can handle the linguistic issues that come from...
Chapter
Digital image watermarking techniques have enabled imperceptible information in images to be hidden to ensure the information can be extracted later from those images. For any watermarking scheme, there are four main requirements which are imperceptibility, Robustness, capacity and security. Recently, hybrid Singular Value Decomposition (SVD) based...
Chapter
Numerous researchers have worked on the knowledge-based semantics of words to clarify the ambiguity of (https://github.com/alimuttaleb/Ali-Muttaleb/blob/master/Synonym.txt) synonyms in various natural-language processing fields, such as Wikipedia, websites, and social networks. This paper attempts to clarify ambiguities in the lexical semantics of...
Chapter
The dimensional phase of Arabic Language, question answering (QA) involves an intrinsic form of question classification (QC) that functions to perform an important task in question answering system (QAS). The purpose of QC is to precisely assign labels to questions that are majorly dependent on the form of answer type. Moreover, classification of u...
Article
Feature extraction is the most important step that affects the recognition accuracy of face recognition. One of these features are the texture descriptors that are playing an important role as local features descriptor in many of the face recognition systems. Recently, many types of texture descriptors had been proposed and used for face recognitio...
Article
Full-text available
Singular Value Decomposition (SVD) comprises many important mathematical properties that are useful in numerous applications. Newly developed SVD-based watermarking schemes can effectively maintain minor changes despite the large altered singular values S caused by the attacks. Due to the stability and the properties of S, most of the researchers p...
Article
In the 21st century, the Arabic language is amongst the most spoken language of all time, having about 300 million speakers in the globe. Thus, Arabic question answering systems are becoming highly needful for the intellectual benefit internet users. Contrary to the need of Arabic Question Answering, there are only a few reports concerning it. In v...
Article
Full-text available
Software testing is required to verify and validate systems. Combinatorial testing in one of the significant testing techniques. Design and select test cases for combinatorial testing considered as combinatorial problem. Even though there are some existing optimization algorithms based combinatorial testing strategies that minimize the number of te...
Article
Full-text available
In this paper, a new texture descriptor inspired from Completed Local Ternary Pattern (CLTP) is proposed and investigated for texture image classification task. A wavelet-CLTP (WCLTP) is proposed by integrating the CLTP with the redundant discrete wavelet transform (RDWT). Firstly, the images are decomposed using RDWT into four sub-bands. Then, the...
Conference Paper
Full-text available
The dimensional phase of Arabic Language, question answering (QA) involves an intrinsic form of question classification (QC) that functions to perform an important task in question answering system (QAS). The purpose of QC is to precisely assign labels to questions that are majorly dependent on the form of answer type. Moreover, classification of u...
Conference Paper
In the 21 st century, the Arabic language is amongst the most spoken language of all time, having about 300 million speakers in the globe. Thus, Arabic question answering systems are becoming highly needful for the intellectual benefit internet users. Contrary to the need of Arabic Question Answering, there are only a few reports concerning it. In...
Article
Full-text available
One of the main challenges in the Automatic Speech Recognition (ASR) is the noise. The performance of the ASR system reduces significantly if the speech is corrupted by noise. In spectrogram representation of a speech signal, after deleting low Signal to Noise Ratio (SNR) elements, the incomplete spectrogram is obtained. In this case, the speech re...
Article
Full-text available
Computer software is in high demand everywhere in the world. The high dependence on software makes software requirements more complicated. As a result, software testing tasks get costlier and challenging due to a large number of test cases, coupled with the vast number of the system requirements. This challenge presents the need for reduction of th...
Article
Many of texture descriptors are proposed based on the Local Binary Pattern (LBP) and have been achieved remarkable texture classification accuracy such as Completed LBP (CLBP) and Completed Local Binary Count (CLBC). However, the LBP suffers from two weaknesses where: 1) it is sensitive to noise and; 2) it sometimes classify two or more different p...
Article
Although image watermarking schemes based on singular value decomposition (SVD) demonstrate high robustness and imperceptibility, they are exposed to the false positive problem (FPP). This drawback mostly occurs when embedding steps depend on singular values while singular vectors are used as secret keys. In this study, a new reliable SVD-based ima...
Article
An ensemble of Enhanced Fuzzy Min Max (EFMM) neural networks for data classification is proposed in this paper. The certified belief in strength (CBS) method is used to formulate the ensemble EFMM model, with the aim to improve the performance of individual EFMM networks. The CBS method is used to measure trustworthiness of each individual EFMM net...
Article
Full-text available
Nowadays, face recognition becomes one of the important topics in the computer vision and image processing area. This is due to its importance where can be used in many applications. The main key in the face recognition is how to extract distinguishable features from the image to perform high recognition accuracy. Local binary pattern (LBP) and man...
Article
Full-text available
The Local Binary Pattern (LBP) texture descriptor and some of its variant descriptors have been successfully used for texture classification and for a few other tasks such as face recognition, facial expression, and texture segmentation. However, these descriptors have been barely used for image categorisation because their calculations are based o...
Article
Digital image watermarking protects content by embedding a signal (i.e., owner information) into the host image without noticeable degradation in visual quality. To develop any image watermarking scheme, there some important requirements should be achieved such as imperceptibly, robustness, capacity, security, and, etc. Generally, the watermarking...
Article
Digital watermarking has been suggested as a way to achieve digital protection. The aim of digital watermarking is to insert the secret data into the image without significantly affecting the visual quality. This study presents a robust block-based image watermarking scheme based on the singular value decomposition (SVD) and human visual system in...
Conference Paper
The Completed Local Ternary Pattern descriptor (CLTP) was proposed to overcome the drawbacks of the Local Binary Pattern (LBP). It used for rotation invariant texture classification and demonstrated superior classification accuracy with different types of texture datasets. In this paper, the performance of CLTP for image categorisation is studied a...
Conference Paper
With easy and quick data distribution over the Internet, copyright protection and authentication become important applications of digital watermarking. The image watermarking schemes that are useful to serve these applications should perform well in some of challenging applications such as print-scan and print-cam (PSPC) applications. This challeng...
Conference Paper
With easy and quick data distribution over the Internet, copyright protection and authentication become important applications of digital watermarking. The image watermarking schemes that are useful to serve these applications should perform well in some of challenging applications such as print-scan and print-cam (PSPC) applications. This challeng...
Article
Full-text available
Interest point detection is an active area in computer vision due to its importance in many applications. Measuring the pixel-wise difference between image pixel intensities is the mechanism of most detectors that have been proposed in literature. Recently, interest point detectors were proposed that incorporated the histogram representation instea...
Article
Full-text available
Despite the fact that the two texture descriptors, the completed modeling of Local Binary Pattern (CLBP) and the Completed Local Binary Count (CLBC), have achieved a remarkable accuracy for invariant rotation texture classification, they inherit some Local Binary Pattern (LBP) drawbacks. The LBP is sensitive to noise, and different patterns of LBP...
Conference Paper
Full-text available
Detecting an interest point in the images to extract the features from it is an important step in many computer vision applications. For good performance, these points have to be robust against any transformation that can be done on the images such as viewpoint change, scaling change, rotation, and illumination and, etc. Many of the suggested inter...
Conference Paper
Full-text available
Classifying the unknown image into the correct related class is the aim of the object class recognition systems. Two main points should be kept in mind to implement a class recognition system. Which descriptors that have a higher discriminative power that needs to be extracted from the images? Which classifier can classify these descriptors success...
Conference Paper
Full-text available
The performance of the Automatic Speech Recognition (ASR) system reduces greatly when speech is corrupted by noise. In spectrogram representation of a speech signal, after deleting low SNR elements, incomplete spectrogram is obtained. In this case, the speech recognizer should make modifications to spectrogram to restore the missing elements, which...

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Projects

Projects (11)
Project
This project aims to: 1. To investigate the parts in the Kidney algorithm to be enhanced. 2. To implement a new hybrid algorithm based on the Kidney-Inspired Algorithm with mutation operator, Jaya Algorithm, and Meeting room Algorithm. Then Implement an IoT test list generator strategy based on the new novel algorithm. 3. To evaluate the performance and the effectiveness of the proposed hybrid algorithm by several optimization problems. as well as in the IoT combinatorial testing problem.
Project
The main aim of this research is to improve the potential performance of deep learning algorithms. This goal can be achieved through the following objectives: 1. To investigate the computational complexity and slow learning limitations of the deep learning algorithms 2. To propose new pre-processing and feature reduction steps to overcome computational complexity and slow learning of deep learning 3. To assess the usefulness of the added proposed stages on the performance of deep learning in medical analysis systems, such as the early-stage AD detection system. 4. Publish the results in international journal ISI / SCOPUS.
Archived project
Software should be tested before released to the market to be sure that the software has been achieved the quality assurance measurement objectives. Therefore. One of the testing types is combinatorial interaction testing (CIT) which is intended to detect the faults that may be occurred between the system feature interactions. The test case generation is the most active area of CIT research. The generation process of the efficient test suite with minimum size from the huge number of test cases can be considered as one of the optimization problem. Thus, several researchers have been addressing the combinatorial interaction testing issues by developing the various strategies based on a search-based approach or a pure-computational approach, although, these are useful, but most of them have a lack to support the constraints combinations during generation the test list. The aim of this research will introduced two new CIT strategies by adapting a greedy algorithm called Greedy Test generation Strategy(GTS). In addition, to enhance the GTS, some modifications to the greedy algorithm will be introduced. Then the new version of GTS strategy will be called a Modified Greedy Test generation Strategy (MGTS). An evaluation will be done to compare the two new strategies’ results to evaluate their performances, and decide which is the best in generating a minimum final test suite size among them?. The expected results will be satisfactory and benchmarked with the existing CIT strategies' results.