The detection of vehicles in airborne downward looking infrared linescan imagery

The system the authors propose uses a novel arrangement of filters (which are readily available in hardware) for detecting and segmenting potential vehicles. A set of vehicle-nonvehicle discriminating features are then extracted and used as the basis for classification. Knowledge of the platform´s position, the sensor geometry and its noise characteristics are exploited to remove unnecessary dimensionality from the feature space and keep the variability of individual features to a minimum. Classifier fusion and hierarchical classification strategies have been compared with standard approaches. The performance of the system is evaluated and problem areas highlighted