Fusion of polarimetric infrared features and GPR features for landmine detection
conference paper
Currently no single sensor reaches the performance requirements for humanitarian landmine detection, Using sensor-fusion methods, multiple sensors can be combined for improved detection performance. This paper focuses on the feature-level fusion procedure for a sensor combination consisting of a polarimetric infrared imaging sensor developed by TNO and a video impulse GPR developed by Delft University of Technology. Feature-level sensor fusion is the process where specific information (i.e. features) from objects detected by different sensors are combined and classified. The single sensor detection methods and the feature-level sensor-fusion methods are evaluated using a leave-one-out evaluation method. This evaluation method provides an independent evaluation set while retaining the largest possible training set. The detection results of both single sensor and the sensor fusion methods are presented in receiver operator chracteristics (ROC) curves. They show that on the training set feature-level sensor-fusion always outperforms the best single sensor. Furthermore, on the independent evaluation set there are ROCpoints of the feature-level sensor-fusion methods that are better than the best sensor.
TNO Identifier
95616
Publisher
IRCT-TR, Delft University of Technology
Source title
Proceedings of the 2nd international workshop on advanced ground penetrating radar, May 14-16, Delft, The Netherlands
Editor(s)
Yarovoy, A.
Place of publication
Delft
Pages
222-227
Files
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