Title :
Wavelet-based position detection of buried pipes from GPR signals by use of angle information
Author :
Kobayashi, Makoto ; Uchikado, Tomohiro ; Nakano, Kazushi
Author_Institution :
Environ. Planning Bur., Yokohama, Japan
Abstract :
There are many metal pipes under paved roads in modern cities. For example, before installing a traffic signal post, underground mapping must take place to avoid hitting buried pipes. We use a ground-penetrating radar (GPR) to resolve this issue. The goal of this research is to detect the positions of buried pipes with GPR signals automatically. In this paper, we propose a new detection method for locating buried pipes. The proposed method consists of two-dimensional Gabor wavelet transform (2D GWT), Delaunay triangulation (DT), particle filter (PF) and polynomial regression (PR). 2D GWT results represent angle information of GPR signals called B-scan. The GWT results are used as a likelihood function for the PF, and the particles ride on and follow the target signal in B-scan. The DT is used for initial particle generation of the PF, and the positions of pipes are detected by using the PR model for expectations of the PF. We show that most positions of pipes are found by using our method. However, the problem of inaccuracy of some detections needs to be enhanced for automatic detection.
Keywords :
ground penetrating radar; mesh generation; pipes; polynomials; radar detection; regression analysis; wavelet transforms; 2D GWT; B-scan; Delaunay triangulation; GPR signals; PR; PR model; angle information; automatic detection; buried pipe location; buried pipes; ground-penetrating radar; metal pipes; particle filter; particle generation; paved roads; polynomial regression; two-dimensional Gabor wavelet transform; wavelet-based position detection; Buried object detection; Ground penetrating radar; Particle filters; Pattern recognition; Permittivity; Polynomials; Wavelet analysis; Delaunay triangulation; Ground-penetrating radar; Particle filter; Position detection; Wavelet transform;
Conference_Titel :
Wavelet Analysis and Pattern Recognition (ICWAPR), 2012 International Conference on
Conference_Location :
Xian
Print_ISBN :
978-1-4673-1534-0
DOI :
10.1109/ICWAPR.2012.6294813