DocumentCode
2061000
Title
Automatic prototype extraction for adaptive OCR
Author
Nagy, George ; Xu, Yihong
Author_Institution
Dept. of Electr. Comput. & Syst. Eng., Rensselaer Polytech. Inst., Troy, NY, USA
Volume
1
fYear
1997
fDate
18-20 Aug 1997
Firstpage
278
Abstract
A Bayesian method of isolating character bitmaps from paragraph-length samples of heavily degraded text images is demonstrated. The method requires a transcript of the text, but it is sufficiently robust to tolerate errors in transcripts obtained from multifont commercial OCR software. The resulting prototypes (labeled character images) are used to recognize additional text an the same document
Keywords
Bayes methods; adaptive signal processing; document image processing; optical character recognition; Bayesian method; adaptive OCR; additional text recognition; automatic prototype extraction; character bitmap isolation; error tolerance; heavily degraded text images; labeled character images; multifont commercial OCR software; paragraph-length samples; text transcript; Bayesian methods; Character recognition; Degradation; Design engineering; Image recognition; Optical character recognition software; Prototypes; Robustness; Systems engineering and theory; Text recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition, 1997., Proceedings of the Fourth International Conference on
Conference_Location
Ulm
Print_ISBN
0-8186-7898-4
Type
conf
DOI
10.1109/ICDAR.1997.619856
Filename
619856
Link To Document