Hybrid shape recognition system with microlens array processor and direct optical input

We present a hybrid shape recognition system with an optical Hough transform preprocessor. A very compact design is achieved by a microlens array processor. Using incoherent light, the processor accepts direct optical input without any extra image converter being required. The microlens array processor is constructed of a crossed assembly of two low-cost plastic lenticular arrays and a Hough transform weight mask. It is integrated in a compact objective barrel, which is attached directly to a CCD-camera like a conventional camera lens. The system delivers one output signal for each of the 64 x 64 microlenses. The resolution of the microlenses and the weight mask results in an extremely high degree of parallelism. It corresponds to a connection of 4k inputs and outputs by 16M weights in parallel. The feature extraction tasks of lower computational complexity and the classification, which can be performed in real-time, are implemented as a neural network on a personal computer.