amal hameed khaleel

@uobasrah.edu.iq

Computer Science Department
University of Basrah

EDUCATION

Master of computer science

RESEARCH INTERESTS

Artificial intelligence, data mining, security, Multimedia processing
13

Scopus Publications

Scopus Publications

  • Multitask Virtual Keyboard Controlled by an Eye-Gaze-Based Intelligent Entry System
    Amal Hameed Khaleel, Thekra Abbas, Abdul-Wahab Sami Ibrahim
    Journal of Computational and Cognitive Engineering, 2025
    In modern society, computers and cell phones play an integral role in individuals' everyday lives. Individuals utilize messaging platforms such as WhatsApp, WeChat, and Facebook daily to communicate with others. Virtual keyboards are a significant tool in assistive technology because they aid individuals with significant motor disabilities in making effective contact with computers. This study proposes an eye-gaze-controlled virtual keyboard using a new method called Distance Eyelid-Iris-MediaPipe, which enables individuals with disabilities to write effectively. The suggested virtual keyboard is an affordable assistive device because it only necessitates a webcam for operation. The proposed virtual keyboard consists of six supplementary menus: two menus for English letters, one for numerical digits and mathematical operations, one for important text operations, one for Latin symbols, and an emoji menu. The suggested keyboard has special characteristics such as auditory feedback and visual highlighting of pressed keys. The testing of the proposed system received positive feedback from several users, and the empirical results of the proposed system were better than those of the previous models. It achieved this with an average typing rate of 18 characters per minute and 4 words per minute, and it had a NASA-TLX score of 10% and a system usability scale score of 93. Received: 27 April 2025| Revised: 25 June 2025| Accepted: 11 July 2025 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data are available on request from the corresponding author upon reasonable request. Author Contribution Statement Amal Hameed Khaleel: Conceptualization, Methodology, Software, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Project administration. Thekra Abbas: Methodology, Validation, Resources, Writing – original draft, Writing – review & editing, Supervision. Abdul-Wahab Sami Ibrahim: Conceptualization, Formal analysis, Investigation, Resources, Writing – review & editing, Supervision.
  • Gaze-Controlled Arabic Virtual Keyboard: Design and Evaluation of a Novel Layout
    Amal Hameed Khaleel, Thekra Abbas
    Ingenierie Des Systemes D Information, 2025
  • A novel convolutional feature-based method for predicting limited mobility eye gaze direction
    Amal Hameed Khaleel, Thekra H Abbas, Abdul-Wahab Sami Ibrahim
    International Journal of Advances in Intelligent Informatics, 2024
    Eye gaze direction is a critical issue since several applications in computer vision technology rely on determining gaze direction, where individuals move their eyes to limited mobility locations for sensory information. Deep neural networks are considered one of the most essential and accurate image classification methods. Several methods of classification to determine the direction of the gaze employ convolutional neural network models, which are VGG, ResNet, Alex Net, etc. This research presents a new method of identifying human eye images and classifying eye gaze directions (left, right, up, down, straight) in addition to eye-closing discrimination. The proposed method (Di-eyeNET) stands out from the developed method (Split-HSV) for enhancing image lighting. It also reduces implementation time by utilizing only two blocks and employing dropout layers after each block to achieve fast response times and high accuracy. It focused on the characteristics of the human eye images, as it is small, so it cannot be greatly enlarged, and the eye's iris is in the middle of the image, so the edges are not important. The proposed method achieves excellent results compared to previous methods, classifying the five directions of eye gaze instead of the four directions. Both the global dataset and the built local dataset were utilized. Compared to previous methods, the suggested method's results demonstrate high accuracy (99%), minimal loss, and the lowest training time. The research benefits include an efficient method for classifying eye gaze directions, with faster implementation and improved image lighting.
  • Best low-cost methods for real-time detection of the eye and gaze tracking
    Amal Hameed Khaleel, Thekra H. Abbas, Abdul-Wahab Sami Ibrahim
    I Com, 2024
    The study of gaze tracking is a significant research area in computer vision. It focuses on real-world applications and the interface between humans and computers. Recently, new eye-tracking applications have boosted the need for low-cost methods. The eye region is a crucial aspect of tracking the direction of the gaze. In this paper, several new methods have been proposed for eye-tracking by using methods to determine the eye area as well as find the direction of gaze. Unmodified webcams can be used for eye-tracking without the need for specialized equipment or software. Two methods for determining the eye region were used: facial landmarks or the Haar cascade technique. Moreover, the direct method, based on the convolutional neural network model, and the engineering method, based on distances determining the iris region, were used to determine the eye’s direction. The paper uses two engineering techniques: drawing perpendicular lines on the iris region to identify the gaze direction junction point and dividing the eye region into five regions, with the blackest region representing the gaze direction. The proposed network model has proven effective in determining the eye’s gaze direction within limited mobility, while engineering methods improve their effectiveness in wide mobility.
  • Enhancing Human-Computer Interaction: A Comprehensive Analysis of Assistive Virtual Keyboard Technologies
    Amal Hameed Khaleel, Thekra HayderAli Abbas, Abdul-Wahab Sami Ibrahim
    Ingenierie Des Systemes D Information, 2023
  • Hiding speech in video using swarm optimization and data mining
    Amal Hameed Khaleel, Iman Qays Abduljaleel
    Aip Conference Proceedings, 2023
  • Multimedia Privacy Protection Based-on Blockchain: Survey
    Bashar M. Nema, Rehab Ajel, Amal Hameed Khaleel, Shatha J. Mohammed
    2nd International Conference on Advanced Computer Applications Aca 2023, 2023
    The use of blockchain technology is one of the latest technologies used to protect digital content. This paper provides a brief overview of Blockchain-based applications for protecting the privacy of audiovisual material within the time period (2015–2021), in which methods of using Blockchain technology alone or in combination with traditional content protection techniques (encryption, digital watermarks, fingerprints, etc.) are presented. Recently, researchers moved towards developing this technology by integrating it with different encryption techniques because the number of content protection systems based on Blockchain technology was few due to the many problems in it. For this reason, we note in this review that the number of research in recent years is much greater than in previous years. This paper discussed the technical challenges, advantages, and disadvantages of each method used in previous research, and outlined future research directions.
  • Speech signal compression and encryption based on sudoku, fuzzy C-means and threefish cipher
    International Journal of Electrical and Computer Engineering, 2021
  • Secure image hiding in speech signal by steganography-mining and encryption
    Amal Hameed Khaleel, Iman Qays Abduljaleel
    Indonesian Journal of Electrical Engineering and Computer Science, 2021
    <span>Information hiding techniques are constantly evolving due to the increased need for security and confidentiality. This paper proposes a working mechanism in three phases. The first phase includes scrambling the values of the gray image depending on a series of keys that are generated using a quantum chaotic map. The second phase generates hybrid keys by mixing a Zaslavsky and a 3D Hanon map that are used to encrypt the gray image values produced after the scramble. Finally, in the third phase, a new algorithm is suggested to hide the encrypted gray image at random locations within a speech file. This algorithm includes the LSB algorithm to determine the hidden bits and the zero-crossing K-means algorithm in selecting locations mining in a scattered manner so that hackers cannot easily retrieve the hidden data of any hacked person. Also used a fractional fourier transform to choose magnitude value as specific data to hide encoded image data. The measures MSE, PSNR, NSCR, and UACI are using to measure the work efficiency in the encryption algorithm, and in measuring the efficiency of the hidden algorithm, use the measures SNR, PSNR, and MSE. The results of the paper are encouraging and efficient compared to other algorithms that performed the same work. Hence our results show the larger the image dimensions used, the better the values.</span>
  • A novel technique for speech encryption based on k-means clustering and quantum chaotic map
    Amal Hameed Khaleel, Iman Qays Abduljaleel
    Bulletin of Electrical Engineering and Informatics, 2021
    In information transmission such as speech information, higher security and confidentiality are specially required. Therefore, data encryption is a pre-requisite for a secure communication system to protect such information from unauthorized access. A new algorithm for speech encryption is introduced in this paper. It depends on the quantum chaotic map and k-means clustering, which are employed in keys generation. Also, two stages of scrambling were used: the first relied on bits using the proposed algorithm (binary representation scrambling BiRS) and the second relied on k-means using the proposed algorithm (block representation scrambling BlRS). The objective test used statistical analysis measures (signal-to-noise-ratio, segmental signal-to-noise-ratio, frequency-weighted signal-to-noise ratio, correlation coefficient, log-likelihood ratio) applied to evaluate the proposed system. Via MATLAB simulations, it is shown that the proposed technique is secure, reliable and efficient to be implemented in secure speech communication, as well as also being characterized by high clarity of the recovered speech signal.
  • Significant medical image compression techniques: A review
    I. Q. Abduljaleel, A. Khaleel
    Telkomnika Telecommunication Computing Electronics and Control, 2021
  • Hiding text in speech signal using K-means, LSB techniques and chaotic maps
    Iman Qays Abduljaleel, Amal Hameed Khaleel
    International Journal of Electrical and Computer Engineering, 2020
  • Hide Medical Images in a Speech Signal using DNA Coding and Fuzzy C-Means
    Iman Qays Abduljaleel, Amal Hameed Khaleel
    Proceedings 2020 2nd Annual International Conference on Information and Sciences Aicis 2020, 2020