Ahmed Barnawi^1,*, Krishan Kumar², Neeraj Kumar¹, Bander Alzahrani¹, Amal Almansour¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 2117-2137, 2024, DOI:10.32604/cmes.2023.044184 - 29 January 2024

Abstract Landmines continue to pose an ongoing threat in various regions around the world, with countless buried landmines affecting numerous human lives. The detonation of these landmines results in thousands of casualties reported worldwide annually. Therefore, there is a pressing need to employ diverse landmine detection techniques for their removal. One effective approach for landmine detection is UAV (Unmanned Aerial Vehicle) based Airborne Magnetometry, which identifies magnetic anomalies in the local terrestrial magnetic field. It can generate a contour plot or heat map that visually represents the magnetic field strength. Despite the effectiveness of this approach,… More >

Fatma M. El-Ghamry^1,2, Walid El-Shafai², Mahmouad I. Abdalla¹, Ghada M. El-Banby³, Abeer D. Algarni^4,*, Moawad I. Dessouky², Adel S. Elfishawy², Fathi E. Abd El-Samie^2,4, Naglaa F. Soliman^1,4

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4457-4487, 2022, DOI:10.32604/cmc.2022.022328 - 14 January 2022

Abstract Recently, ground-penetrating radar (GPR) has been extended as a well-known area to investigate the subsurface objects. However, its output has a low resolution, and it needs more processing for more interpretation. This paper presents two algorithms for landmine detection from GPR images. The first algorithm depends on a multi-scale technique. A Gaussian kernel with a particular scale is convolved with the image, and after that, two gradients are estimated; horizontal and vertical gradients. Then, histogram and cumulative histogram are estimated for the overall gradient image. The bin values on the cumulative histogram are used for More >