Machine-printed character recognition revisited: re-application of recent advances in handwritten character recognition research

Abstract

The increasing automation of document processing applications has emphasised the need for robust and reliable recognition of machine-printed characters. Although research in character recognition is now focused principally on applications in reading handwritten characters, this paper demonstrates how recent progress in the area of multiple-expert classification can be exploited to provide new approaches to the processing of printed data. Established classification algorithms have been used in a new multiple-expert framework to generate an optimised decision combination platform comprising multiple experts, and significant improvements in overall recognition performance on machine-printed characters have been achieved.