Automatic localization of gas pipes from GPR imagery. Terrasse, G., Nicolas, J., Trouvé, E., & Drouet, É. In 2016 24th European Signal Processing Conference (EUSIPCO), pages 2395-2399, Aug, 2016.
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Paper doi abstract bibtex
Paper doi abstract bibtex In order to improve asset knowledge and avoid third part damages during road works, the localization of gas pipes in a non-destructive way has become a wide domain of research during these last years. Several devices have been developed in order to answer this problem. Acoustic, electromagnetic or RFID technologies are used to find pipes in the underground. Ground Penetrating Radar (GPR) is also used to detect buried gas pipes. However it does not directly provide a 3D position but a reflection map called B-scan that the user must interpret. In this paper, we propose a novel method to automatically get the position of gas pipes with GPR acquisitions. This method uses a dictionary of theoretical pipe signatures. The correlation between each atom from the dictionary and the B-scan is used as feature in a two part supervised learning scheme. Our method has been applied to real data acquired on a test area and in real condition. The proposed method presents satisfying qualitative and quantitative results compared to other methods.
@InProceedings{7760678,
author = {G. Terrasse and J. Nicolas and E. Trouvé and É. Drouet},
booktitle = {2016 24th European Signal Processing Conference (EUSIPCO)},
title = {Automatic localization of gas pipes from GPR imagery},
year = {2016},
pages = {2395-2399},
abstract = {In order to improve asset knowledge and avoid third part damages during road works, the localization of gas pipes in a non-destructive way has become a wide domain of research during these last years. Several devices have been developed in order to answer this problem. Acoustic, electromagnetic or RFID technologies are used to find pipes in the underground. Ground Penetrating Radar (GPR) is also used to detect buried gas pipes. However it does not directly provide a 3D position but a reflection map called B-scan that the user must interpret. In this paper, we propose a novel method to automatically get the position of gas pipes with GPR acquisitions. This method uses a dictionary of theoretical pipe signatures. The correlation between each atom from the dictionary and the B-scan is used as feature in a two part supervised learning scheme. Our method has been applied to real data acquired on a test area and in real condition. The proposed method presents satisfying qualitative and quantitative results compared to other methods.},
keywords = {data acquisition;ground penetrating radar;learning (artificial intelligence);radar imaging;telecommunication computing;gas pipe automatic localization;GPR imagery;asset knowledge improvement;third-part damage avoidance;RFID technology;electromagnetic technology;acoustic technology;ground penetrating radar;buried gas pipe detection;B-scan;reflection map;GPR acquisition;two-part supervised learning scheme;Dictionaries;Ground penetrating radar;Shape;Supervised learning;Correlation;Clutter;Computational modeling;Gas pipes localization;GPR;Dictionary;Supervised learning},
doi = {10.1109/EUSIPCO.2016.7760678},
issn = {2076-1465},
month = {Aug},
url = {https://www.eurasip.org/proceedings/eusipco/eusipco2016/papers/1570251626.pdf},
}Downloads: 0
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