OCR error correction using a noisy channel model

Abstract

In this paper, we take a pattern recognition approach to correcting errors in text generated from printed documents using optical character recognition (OCR). We apply a very general, theoretically optimal model to the problem of OCR word correction, introduce practical methods for parameter estimation, and evaluate performance on real data.