Fast Detection of Ground Penetrating Radar Objects Based on Cross Correlation and Hough Transform

Considering the issue of low computation efficiency of Ground Penetrating Radar (GPR) object detection method, a fast algorithm is proposed based on the spatial distribution of reflected energy, which is modeled as a three-parameter hyperbola. A reflection hyperbola is first extracted by utilizing the correlation between adjacent reflections. Being weighted with reflection energy, the hyperbola is then fitted to estimate the two parameters of the reflected model. Finally, the object detection and localization task is completed with one dimensional Hough transform. The efficiency of the proposed algorithm is demonstrated both theoretically and experimentally. Compared with the traditional algorithm based on Hough transform, the proposed algorithm consumes only 1.5% computational time without sacrificing the detection and localization performance.