4 February 2013 Post processing with first- and second-order hidden Markov models
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In this paper, we present the implementation and evaluation of first order and second order Hidden Markov Models to identify and correct OCR errors in the post processing of books. Our experiments show that the first order model approximately corrects 10% of the errors with 100% precision, while the second order model corrects a higher percentage of errors with much lower precision.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kazem Taghva, Kazem Taghva, Srijana Poudel, Srijana Poudel, Spandana Malreddy, Spandana Malreddy, } "Post processing with first- and second-order hidden Markov models", Proc. SPIE 8658, Document Recognition and Retrieval XX, 865814 (4 February 2013); doi: 10.1117/12.2006500; https://doi.org/10.1117/12.2006500


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