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Proceedings Paper

Optimal forward regression for landmine detection by thermal sensing
Author(s): Luca Del Vecchio; Paolo Fallavollita; Simone De Marco; Salvatore Esposito; Marco Balsi; Stanislaw Jankowski
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Paper Abstract

In this paper, starting from the GOFR algorithm, a new Forward Regression algorithm for landmine detection and localization using thermal methods is presented. The efficiency of such algorithm is described by showing a valid representation of the typical temperature waveforms taken after heating the ground surface, and detection of temperature anomalies due to the presence of hidden objects. Optimizations to the algorithm are then showed, with the aim of a significant sampling density reduction in space and time.

Paper Details

Date Published: 15 September 2010
PDF: 7 pages
Proc. SPIE 7745, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2010, 77451R (15 September 2010); doi: 10.1117/12.873405
Show Author Affiliations
Luca Del Vecchio, Univ. degli Studi di Roma La Sapienza (Italy)
Paolo Fallavollita, Univ. degli Studi di Roma La Sapienza (Italy)
Simone De Marco, Univ. degli Studi di Roma La Sapienza (Italy)
Salvatore Esposito, Univ. degli Studi di Roma La Sapienza (Italy)
Marco Balsi, Univ. degli Studi di Roma La Sapienza (Italy)
Stanislaw Jankowski, Warsaw Univ. of Technology (Poland)


Published in SPIE Proceedings Vol. 7745:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2010
Ryszard S. Romaniuk, Editor(s)

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