DocumentCode
2021618
Title
Cryptogram Decoding for OCR Using Numerization Strings
Author
Huang, Gary ; Learned-Miller, Erik ; McCallum, Andrew
Author_Institution
Univ. of Massachusetts, Amherst
Volume
1
fYear
2007
fDate
23-26 Sept. 2007
Firstpage
208
Lastpage
212
Abstract
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.
Keywords
cryptography; document image processing; optical character recognition; pattern clustering; OCR; character models; cryptogram decoding; font styles; numerization strings; printed documents; Computer science; Cryptography; Hamming distance; Hidden Markov models; Image coding; Ink; Intrusion detection; Iterative decoding; Optical character recognition software; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition, 2007. ICDAR 2007. Ninth International Conference on
Conference_Location
Parana
ISSN
1520-5363
Print_ISBN
978-0-7695-2822-9
Type
conf
DOI
10.1109/ICDAR.2007.4378705
Filename
4378705
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