Post Processing with First- and Second-Order Hidden Markov Models
Document Type
Conference Proceeding
Publication Date
2-4-2013
Publication Title
Proceedings of SPIE 8658
Publisher
SPIE
Abstract
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.
Keywords
Hidden Markov models; Optical character recognition; Optical character recognition devices
Disciplines
Civil and Environmental Engineering | Computer Engineering | Engineering
Language
English
Permissions
Use Find in Your Library, contact the author, or interlibrary loan to garner a copy of the item. Publisher policy does not allow archiving the final published version. If a post-print (author's peer-reviewed manuscript) is allowed and available, or publisher policy changes, the item will be deposited.
Repository Citation
Taghva, K.,
Poudel, S.,
Malreddy, S.
(2013).
Post Processing with First- and Second-Order Hidden Markov Models.
Proceedings of SPIE 8658
SPIE.
http://dx.doi.org/10.1117/12.2006501