Machine-printed from handwritten text discrimination

This paper deals with the discrimination between machine-printed and handwritten text, a prerequisite for many OCR applications. An easy-to-follow approach is proposed based on an integrated system able to localize text areas and split them in text-lines. A set of simple structural characteristics that capture the differences between machine-printed and handwritten text-lines is presented and preliminary experiments on document images taken from databases of different languages and characteristics show a remarkable performance.