Model, predict and test: Towards a rigorous process for acquisition of object detection and recognition algorithms for un-manned air vehicle applications

The designers of unmanned air vehicle (UAV) mission systems are seeking to exploit advances in consumer image processing technology, to provide additional object detection and recognition capability for UAV systems. However, the two application domains are quite different, so a simple transfer of algorithms is not possible. A formal approach for selecting and developing algorithms is proposed. This involves algorithm modelling and experimental validation by the algorithm supplier, together with assessment trials in a representative system, carried out by the system designer. The objective is to build confidence in the behaviour of the algorithm under consideration, to build high fidelity models that can be used in system design studies and to address integration issues early in a development programme. A review of the open literature indicates that the necessary algorithm modelling is feasible and an example is presented to illustrate the proposed approach.