Recognizing handwritten text

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Abstract
Notebook computers, using stylus input, are currently a hot topic among PC manufacturers. Handwriting recognition may be an important component of such systems, but only if everyday sloppy handwriting can be accommodated. If recognizes require unnaturally neat or boxed character input, such systems may fail in the marketplace. Neural nets have shown excellent performance at handwriting recognition. I present three neural net approaches to recognizing lines of English texti one using 2D image input, one using stroke sequence input, and one using context to combine the outputs of the other two networks. These networks can be combined to form a recognition engine that will handle natural lines of handwritten English text, including handprint, cursive script, and mixtures of both.

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