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.
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© 2012 IFIP International Federation for Information Processing
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Janning, R., Horváth, T., Busche, A., Schmidt-Thieme, L. (2012). GamRec: A Clustering Method Using Geometrical Background Knowledge for GPR Data Preprocessing. In: Iliadis, L., Maglogiannis, I., Papadopoulos, H. (eds) Artificial Intelligence Applications and Innovations. AIAI 2012. IFIP Advances in Information and Communication Technology, vol 381. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33409-2_36
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DOI: https://doi.org/10.1007/978-3-642-33409-2_36
Publisher Name: Springer, Berlin, Heidelberg
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