Multifont character recognition by 9×9 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 9×9 DPCNN board is presented.