Texture features for antitank landmine detection using ground penetrating radar

Journal Article

In this paper, we consider the application of texture features for antitank landmine detection in ground-penetrating-radar data in the difficult scenario of very high clutter environments. In particular, we develop a technique for 3-D texture feature extraction, and we compare the results for landmine/clutter discrimination using classifiers that are built on 3-D as well as on 2-D texture feature sets. Our results indicate performance improvements across several different challenging testing scenarios when using the relevance-vector-machine classifiers that are trained on our 3-D feature sets as compared to the performance using the 2-D texture feature sets. © 2007 IEEE.

Full Text

Duke Authors

Cited Authors

  • Torrione, P; Collins, LM

Published Date

  • July 1, 2007

Published In

Volume / Issue

  • 45 / 7

Start / End Page

  • 2374 - 2382

International Standard Serial Number (ISSN)

  • 0196-2892

Digital Object Identifier (DOI)

  • 10.1109/TGRS.2007.896548

Citation Source

  • Scopus