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
Scopus Publications
Scopus Publications
Amal Hameed Khaleel and Thekra Abbas
International Information and Engineering Technology Association
Amal Hameed Khaleel, Thekra H Abbas, and Abdul-Wahab Sami Ibrahim
Universitas Ahmad Dahlan
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.
Amal Hameed Khaleel, Thekra H. Abbas, and Abdul-Wahab Sami Ibrahim
Walter de Gruyter GmbH
Abstract 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.
Amal Hameed Khaleel, Thekra HayderAli Abbas, and Abdul-Wahab Sami Ibrahim
International Information and Engineering Technology Association
Amal Hameed Khaleel and Iman Qays Abduljaleel
AIP Publishing
Bashar M. Nema, Rehab Ajel, Amal Hameed Khaleel, and Shatha J. Mohammed
IEEE
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.
Amal Hameed Khaleel and Iman Qays Abduljaleel
Institute of Advanced Engineering and Science
<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>
Amal Hameed Khaleel and Iman Qays Abduljaleel
Institute of Advanced Engineering and Science
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.
I. Q. Abduljaleel and A. Khaleel
Telemedicine applications allow the patient and doctor to communicate with each other through network services. Several medical image compression techniques have been suggested by researchers in the past years. This review paper offers a comparison of the algorithms and the performance by analysing three factors that influence the choice of compression algorithm, which are image quality, compression ratio, and compression speed. The results of previous research have shown that there is a need for effective algorithms for medical imaging without data loss, which is why the lossless compression process is used to compress medical records. Lossless compression, however, has minimal compression ratio efficiency. The way to get the optimum compression ratio is by segmentation of the image into region of interest (ROI) and non-ROI zones, where the power and time needed can be minimised due to the smaller scale. Recently, several researchers have been attempting to create hybrid compression algorithms by integrating different compression techniques to increase the efficiency of compression algorithms.
Iman Qays Abduljaleel and Amal Hameed Khaleel
Institute of Advanced Engineering and Science
In this paper, a new technique that hides a secret text inside a speech signal without any apparent noise is presented. The technique for encoding the secret text is through first scrambling the text using Chaotic Map, then encoding the scraped text using the Zaslavsky map, and finally hiding the text by breaking the speech signal into blocks and using only half of each block with the LSB, K-means algorithms. The measures (SNR, PSNR, Correlation, SSIM, and MSE) are used on various speech files (“.WAV”), and various secret texts. We observed that the suggested technique offers high security (SNR, PSNR, Correlation, and SSIM) of an encrypted text with low error (MSE). This indicates that the noise level in the speech signal is very low and the speech purity is high, so the suggested method is effective for embedding encrypted text into speech files.
Iman Qays Abduljaleel and Amal Hameed Khaleel
IEEE
Medical images possess great privacy, as the patient's information must be completely confidential if it is transferred from one hospital to another via a hospital intranet or the internet to take medical consultations by specialized doctors. This paper presents a safe new method to transfer medical images by hiding them within a speech signal file, and this is done at three levels: First, a scrambling algorithm proposal to ensure a change in the original medical image based on the binary representation of the image values and using the Zaslavsky map, the second level is encryption the scrambled image relying on DNA coding and a series of keys generated by a proposed hybrid algorithm based on (Tinkerbelle map and 3D Henon) that provided us with good image distortion and provided difficulty in retrieving it by any intruder. The last level is to hide the contents of encrypted medical images in a speech signal depending on (integer wavelet transform and LSB algorithm), then using the proposed algorithm based on (fuzzy c-means clustering algorithm and short-time energy) to determine the locations of speech to hide in it. The results of this paper showed that using statistical measures of hiding and encryption were good in maintaining the confidentiality of medical image information compared to previous researches. Consequently, the use of encryption and hiding techniques together has provided double protection against the problems of malicious manipulation and privacy leakage on the internet as well as lack the hospital's intranet to security tools.