Title :
Detecting Curved Underground Tunnels using Partial Radon Transforms
Author :
Gurbuz, A.C. ; McClellan, James H. ; Scott, Waymond R.
Author_Institution :
Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
The Radon transform (RT) is known to be effective in detecting lines in noisy images, but it is not capable of detecting curves unless the curve parametrization is given. In this paper, partial Radon transforms (PRT) are investigated as a tool to detect curved features such as underground tunnels in ground penetrating radar (GPR) images. The algorithm applies the Radon transform to small batches of the total image and updates the tunnel position parameters as new batches are used. Missing data, as well as finding the ends of tunnels can be handled with the proposed algorithm. Performance analysis is given for various signal-to-noise ratios (SNR) and batch sizes. The effect of the curvature level on the performance is also analyzed.
Keywords :
Radon transforms; object detection; GPR images; curve parametrization; curved underground tunnel detection; ground penetrating radar; partial Radon transforms; signal-to-noise ratios; Algorithm design and analysis; Buried object detection; Computer vision; Ground penetrating radar; Performance analysis; Radar detection; Reflection; Shape; Signal analysis; Signal to noise ratio; Radon transforms; curve estimation; partial Radon Transform; tunnel detection;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0727-3
DOI :
10.1109/ICASSP.2007.365965