Image processing of ground penetrating radar data for landmine detection

This paper presents and compares two established methods for the automatic detection of landmines in ground penetrating radar (GPR) data. B-scan data of standard GPR targets and simulant landmines were collected from indoor sand and soil lanes. The images were pre-processed and the least squares method and the Hough transform were applied to objects of interest for the detection of hyperbolic signatures in the data. One drawback of the Hough transform is that it can be computationally expensive as it requires a search in 4-D space for hyperbolic shapes. In this case, it has been simplified so only a search in 1-D space is required, however this simplification did result in some missed detections.

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