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Gauss Gradient and SURF Features for Landmine Detection from GPR Images

Computers, Materials & Continua 2022年第6期71卷 4457-4486页

作者： Fatma M.El-Ghamry Walid El-Shafai Mahmouad I.Abdalla Ghada M.El-Banby Abeer D.Algarni Moawad I.Dessouky Adel S.Elfishawy Fathi E.Abd El-Samie Naglaa F.Soliman Department of Electronics and Communications Engineering Faculty of EngineeringZagazig UniversityZagazigSharqia44519Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

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 discrimination between images with and without landmines.Moreover,a neural classifier is used to classify images with cumulative histograms as feature vectors.The second algorithm is based on scale-space analysis with the number of speeded-up robust feature(SURF)points as the key parameter for classification.In addition,this paper presents a framework for size reduction of GPR images based on decimation for efficient storage.The further classification steps can be performed on images after interpolation.The sensitivity of classification accuracy to the interpolation process is studied in detail.

关键词： GPR images cumulative histogram gradient image neural classifier SURF

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