A new variant on key feature object recognition is presented. It is applied to optimal matching problems involving 2D line segment models and data. A single criterion function ranks both key features and complete object model matches. Empirical studies suggest that the key feature algorithm has run times which are dramatically less than a more general random starts local search algorithm. However, they also show the key feature algorithm to be brittle: failing on some apparently simple problems, while local search appears to be robust