Abstract : GPR is a nondestructive method to scan the subsurface. On the resulting radargrams, originally interpreted manually in a time consuming process, one can see hyperbolas corresponding to buried objects. For accelerating the interpretation a machine shall be enabled to recognize hyperbolas on radargrams autonomously. One possibility is the combination of clustering with an expectation maximization algorithm. However, there is no suitable clustering algorithm for hyperbola recognition. Hence, we propose a clustering method specialized for this problem. Our approach is a directed shape based clustering combined with a sweep line algorithm. In contrast to other approaches our algorithm finds hyperbola shaped clusters and is (1) able to recognize intersecting hyperbolas, (2) noise robust and (3) does not require to know the number of clusters in the beginning but it finds this number. This is an important step towards the goal to fully automatize the buried object detection.
Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-381 (Part I), pp.347-356, 2012, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-33409-2_36〉
https://hal.inria.fr/hal-01521396
Contributeur : Hal Ifip
<>
Soumis le : jeudi 11 mai 2017 - 17:10:19
Dernière modification le : jeudi 26 juillet 2018 - 15:36:03
Document(s) archivé(s) le : samedi 12 août 2017 - 13:45:56
Ruth Janning, Tomáš Horváth, Andre Busche, Lars Schmidt-Thieme. GamRec: A Clustering Method Using Geometrical Background Knowledge for GPR Data Preprocessing. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-381 (Part I), pp.347-356, 2012, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-33409-2_36〉. 〈hal-01521396〉
