Intelligent OCR processing
Wei Ping Sun, Lon‐Mu Liu, Weining Zhang, John Craig Comfort · Journal of the American Society for Information Science · 1992
Optical Character Recognition (OCR) has become a highly demanded information transfer technology in recent years. A problem of current OCR technology is that texts produced by the state-of-the-art OCR software contain an unacceptable frequency of errors. This prevents the OCR technology from being efficiently used for vast-volume information transfer or daily office operation applications. To correct these errors in a conventional way requires a significant amount of costly human-machine interaction. In this article, we identify and classify the types and distributions of optical recognition errors. We proposed a novel post-processing strategy, based on machine learing techniques, to correct errors resulted from unrecognized process