Digital image processor

Image analysis – Learning systems – Neural networks

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382158, 706 29, 706 16, G06K 962

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active

061481017

ABSTRACT:
Taking into consideration the disadvantage that a large-scale analog neural network cannot be constructed as an LSI and, even if this were possible, the cost would be prohibitive and the network would lack universality, a digital image processor for processing input image data based upon a cellular neural network is provided with a first multiply-and-accumulate arithmetic unit for digitally processing multiplication and accumulation of input image data of a plurality of pixels and input weighting values in a predetermined area, a second multiply-and-accumulate arithmetic unit for digitally processing multiplication and accumulation of output image data of a plurality of pixels and output weighting values in a predetermined area, and a non-linear acting unit for deciding output image data in accordance with results of calculation from the first and second multiply-and-accumulate arithmetic unit and non-linear characteristic parameters. This makes it possible to realize an image processor which excels in universality, ease of control and ease of integration.

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Crounse, "Image Halftoning with Cellular Neural Networks", IEEE Transactions on Circuits and Systems II, 40(1993) Apr., No. 4, New York, US.

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