An Application of Neural Net Chips: Handwritten Digit Recognition.

A general purpose, fully-interconnected neural-net chip has been used to perform computationally intensive tasks for handwritten digit recognition. The chip has nearly 3000 programmable connections which can be set for template matching. The templates can be reprogrammed as needed during the recognition sequence. The recognition process proceeds in four major steps. First, the image is captured using a TV camera and a digital framegrab. This image is converted, using a digital computer, to either black or white pixels and scaled to fill a 16x16 pixel frame. Next, using the neural-net chip, the image is skeletonized i.e. the image is thinned to a backbone one pixel wide.