Breejen, E. den
TNO Fysisch en Elektronisch Laboratorium
|Source:||Dubey, A.C.Harvey, J.F.Broach, J.T.et al, Detection and Remediation Technologies for Mines and Minelike Targets V, Part Two, 24-28 April 2000, Orlando, FL, USA, 792-803|
|Proceedings of SPIE|
Physics · Land mine detection · Cameras · Infrared imaging · Metal detectors · Optimization · Radar target recognition · Dempster-Shafer detection · Naive Bayes detection · Voting detection · Sensor data fusion
To acquire detection performance required for an operational system for the detection of anti-personnel landmines, it is necessary to use multiple sensors and sensor-fusion techniques. This paper describes five decision-level sensor-fusion techniques and their common optimisation method. The performance of the sensor-fusion techniques is evaluated by means of Receiver Operator Characteristics curves. These techniques are tested on an outdoor test facility. Three of four test lanes of this facility are used as training set and the fourth is used as evaluation set. The detection performance of naive Bayes, Dempster-Shafer, voting and linear discriminant are very similar on both the training and the evaluation set. This is probably caused by the flexibility of the sensor-fusion techniques resulting into similar optimal solutions independent of the fusion technique.