Multifont character recognition by 9/spl times/9 DPCNN board

Cellular neural networks are a remarkable artificial neural network class well suited for real time image processing tasks. In fact, the parallel analogue computing feature makes them really effective in such problems which require a real time response. Moreover, the limited amount of interconnections relative to cell's neighbourhood only, lend themselves to easy VLSI implementation. In previous papers, the authors presented some CNN hardware. Therefore, in this paper, an algorithm for character recognition developed on the 9/spl times/9 DPCNN board is presented.