Assessment of model-based automatic target recognition on recorded and simulated infrared imagery

During a previous technology programme, a simple landscape and complex target geometries were modelled and demonstrated in a COTS infrared (IR) simulation tool. A preliminary assessment of training-based ATR on real and synthetic imagery was performed, which was presented at SPIE D&S in 2005. The current technology programme has assessed model-based ATR on real and synthetic IR imagery for a 5-class case. Real IR imagery was recorded during a flight campaign. A complex landscape and complex targets were modelled and simulated in a wide variety of conditions in the IR simulation tool. A survey was conducted regarding the current state-of-the-art of model-based ATR approaches. Another survey concerning contour extraction methods for ATR was performed. The best ATR algorithms and contour extraction methods were selected from the survey results. These algorithms were implemented for a multi-class ATR case and adapted to work on the characteristics of IR imagery. The algorithms were benchmarked and compared on the simulated and recorded IR imagery using classical measures. A process for performance assessment of multi-class ATR methods was defined according to an ATR benchmarking concept developed by the German Fraunbofer Research Institute. The assessment was then conducted on the algorithms using a multi-class evaluation approach.