Support vector machines (SVM) present very interesting features in the field of image processing, but the intensive
calculation needed complicates its use in real-time applications. We present an architecture for a SVM which simplifies
most of the calculus using an optoelectronic matrix-vector multiplier (OMVM).
In this paper we present the scheme for a control circuit used in an image processing system which is to be
implemented in a neural network which has a high level of connectivity and reconfiguration of neurons for integration
and trigger based on the Address-Event Representation. This scheme will be employed as a pre-processing stage for a
vision system which employs as its core processing an Optical Broadcast Neural Network (OBNN). [Optical
Engineering letters 42 (9), 2488(2003)]. The proposed vision system allows the possibility to introduce patterns from
any acquisition system of images, for posterior processing.
In this paper we investigate a hardware Pulse Couple Neural Network (PCNN) to be used as the pre-processing stage for a vision system which uses as processing core the Optical Broadcast Neural Network (OBNN) Processor [Optical Engineering Letters 42 (9), 2488 (2003)]. The temporal patterns are to remain constant independently of the position of the spatial pattern in the input image and its orientation. The objective is to obtain synchronous temporal patterns, with fixed pulse rates, from a determined spatial pattern.
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