Anas M. Aloraiqat
Verified @zu.edu.jo
Computer Science
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Science, Artificial Intelligence, Computer Graphics and Computer-Aided Design
Scopus Publications
Scopus Publications
Anas M. Al-Oraiqat, Oleksandr Drieiev, Hanna Drieieva, Yelyzaveta Meleshko, Hazim AlRawashdeh, Karim A. Al-Oraiqat, Yassin M. Y. Hasan, Noor Maricar, and Sheroz Khan
Springer Science and Business Media LLC
Anas M. Al-Oraiqat, Tetiana Smirnova, Oleksandr Drieiev, Oleksii Smirnov, Liudmyla Polishchuk, Sheroz Khan, Yassin M. Y. Hasan, Aladdein M. Amro, and Hazim S. AlRawashdeh
MDPI AG
Computer vision and image processing techniques have been extensively used in various fields and a wide range of applications, as well as recently in surface treatment to determine the quality of metal processing. Accordingly, digital image evaluation and processing are carried out to perform image segmentation, identification, and classification to ensure the quality of metal surfaces. In this work, a novel method is developed to effectively determine the quality of metal surface processing using computer vision techniques in real time, according to the average size of irregularities and caverns of captured metal surface images. The presented literature review focuses on classifying images into treated and untreated areas. The high computation burden to process a given image frame makes it unsuitable for real-time system applications. In addition, the considered current methods do not provide a quantitative assessment of the properties of the treated surfaces. The markup, processed, and untreated surfaces are explored based on the entropy criterion of information showing the randomness disorder of an already treated surface. However, the absence of an explicit indication of the magnitude of the irregularities carries a dependence on the lighting conditions, not allowing to explicitly specify such characteristics in the system. Moreover, due to the requirement of the mandatory use of specific area data, regarding the size of the cavities, the work is challenging in evaluating the average frequency of these cavities. Therefore, an algorithm is developed for finding the period of determining the quality of metal surface treatment, taking into account the porous matrix, and the complexities of calculating the surface tensor. Experimentally, the results of this work make it possible to effectively evaluate the quality of the treated surface, according to the criterion of the size of the resulting irregularities, with a frame processing time of 20 ms, closely meeting the real-time requirements.
Anas M. Al-Oraiqat, Oleksandr S. Ulichev, Yelyzaveta V. Meleshko, Hazim S. AlRawashdeh, Oleksii O. Smirnov, and Liudmyla I. Polishchuk
Springer Science and Business Media LLC
Saleh Daqamseh, A’kif Al-Fugara, Biswajeet Pradhan, Anas Al-Oraiqat, and Maan Habib
MDPI AG
In this study, a multi-linear regression model for potential fishing zone (PFZ) mapping along the Saudi Arabian Red Sea coasts of Yanbu’ al Bahr and Jeddah was developed, using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data derived parameters, such as sea surface salinity (SSS), sea surface temperature (SST), and chlorophyll-a (Chl-a). MODIS data was also used to validate the model. The model expanded on previous models by taking seasonal variances in PFZs into account, examining the impact of the summer, winter, monsoon, and inter-monsoon season on the selected oceanographic parameters in order to gain a deeper understanding of fish aggregation patterns. MODIS images were used to effectively extract SSS, SST, and Chl-a data for PFZ mapping. MODIS data were then used to perform multiple linear regression analysis in order to generate SSS, SST, and Chl-a estimates, with the estimates validated against in-situ data obtained from field visits completed at the time of the satellite passes. The proposed model demonstrates high potential for use in the Red Sea region, with a high level of congruence found between mapped PFZ areas and fish catch data (R2 = 0.91). Based on the results of this research, it is suggested that the proposed PFZ model is used to support fisheries in determining high potential fishing zones, allowing large areas of the Red Sea to be utilized over a short period. The proposed PFZ model can contribute significantly to the understanding of seasonal fishing activity and support the efficient, effective, and responsible use of resources within the fishing industry.
Anas M. Al-Oraiqat, Evgeniy A. Bashkov, and Sergii A. Zori
Springer Science and Business Media LLC
Anas M. Al-Oraiqat and Sergii A. Zori
Springer Science and Business Media LLC
Piotr A. Kisała, Evgeniy Bashkov, Sergii A. Zori, Akmaral Tleshova, and Anas M. Al-Oraiqat
SPIE
The article considers experience of creating of system of realistic 3D stereo visualization by raytracing method on GPU basis. The basic organization of such 3D stereo visualization systems and parallel architecture of computing systems for realistic synthesis of stereo images by raytracing method were proposed. The developed architecture of 3D stereo visualization systems is able to solve the problem associated with middle 3D scene complexity image synthesis in real-time mode.