Cryptogram decoding for optical character recognition
Gary B. Huang, Erik Learned-Miller, Andrew McCallum · ScholarWorks@UMassAmherst (University of Massachusetts Amherst) · 2006
OCR systems for printed documents typically require large numbers of font styles and character models to work well. When given an unseen font, performance degrades even in the absence of noise. In this paper, we perform OCR in an unsupervised fashion without using any character models by using a cryptogram decoding algorithm. We present results on real and artificial OCR data.