Buried Objects Segmentation and Detection in GPR B Scan Images

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Abstract:

Identification of buried objects through Ground Penetrating Radar B scan (GPR-B) images needs high computational techniques and long processing time due to curve fitting or pattern recognition methods. In this study, an efficient and fast recognition system is proposed for detection of buried objects region. Previously, GPR-B scan images of objects with different shapes in various depths were obtained by using gprMax simulation program. The detection process is categorized into four steps. The GPR-B images are transformed at first step. Then, they are thresholded to obtain potential buried object regions. Third step of the system is hough transform in order to eliminate ground surface. Finally, an estimated region analysis is performed. The results show high performance with fully automatic segmentation. The processing time for detection of buried object is in the range of 1.234 - 2.232 seconds. It can be observed that this technique is faster than other studies in the literature. Consequently, it may be used in real time applications for GPR devices.

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