  This article deals with the fusion of flaw detections from multi-sensor
nondestructive materials testing. Because each testing method makes use of
different physical effects for defect localization, a multi-method approach is
promising to effectively distinguish the many false alarms from actual material
defects. To this end, we propose a new fusion technique for scattered two- or
three-dimensional location data. Using a density-based approach, the proposed
method is able to explicitly address the localization uncertainties such as
registration errors. We provide guidelines on how to set all key parameters and
demonstrate the technique's robustness. Finally, we apply our fusion approach
to experimental data and demonstrate its ability to find small defects by
substantially reducing false alarms under conditions where no single-sensor
method is adequate.
