Title :
Fuzzy shell clustering and pipe detection in ground penetrating radar data
Author :
Ciochetto, G. ; Delbò, S. ; Gamba, P. ; Roccato, D.
Author_Institution :
CSELT, Torino, Italy
Abstract :
In this paper a method for hyperbolic target detection in subsurface radar images is presented. The method is based on a suitable fuzzy clustering approach aimed to individuate partially masked and/or corrupted target signatures by exploiting a fuzzy-shell algorithm. Fuzzy logic allows to exploit as much as possible the information hidden in the data, while the robust clustering approach provides a way not only to detect, but also to validate the results obtained. The procedure is applied, with an overall correct classification rate of 84%, to actual GPR data at 400 MHz
Keywords :
buried object detection; fuzzy logic; image classification; pattern clustering; radar detection; radar imaging; 400 MHz; classification rate; corrupted target signatures; fuzzy logic; fuzzy shell clustering; ground penetrating radar data; hyperbolic target detection; partially masked signatures; pipe detection; robust clustering; subsurface radar; Acoustic reflection; Clustering algorithms; Fuzzy logic; Ground penetrating radar; Image analysis; Noise reduction; Radar detection; Shape; Signal processing algorithms; Soil;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International
Conference_Location :
Hamburg
Print_ISBN :
0-7803-5207-6
DOI :
10.1109/IGARSS.1999.771581
