Model based object recognition and object localization are fundamental problems in industrial automation. We present techniques which use a scanner composed of binary light beam sensors to quickly recognize objects (as fast as 5 microseconds) and to accurately localize objects (0.025 millimeters), and we describe localization and recognition experiments and present results. Binary sensors only sense whether the part is present or absent at a particular location, and their high performance is due to their simple specification. Fast recognition is achieved by using indexing to solve the correspondence problem, the problem of interpreting the sensed data as model features; indexing involves using the sensed data to directly look up the correspondence information using a precomputed indexing table. Since each experiment only produces a single indexing vector, indexing tables need to be complete; in this paper we detail a complete indexing construction method for flat polygonal and polyhedral objects.