Bibtex entry:

@inproceedings{icpr96:Kov,
   key = {icpr96:Kov},
   keywords = {ocr, pattern recognition, form processing, classifiers,
               algorithms, nearest neighbors},
   author = {Zs. M. Kovacs-V.},
   title = {A System for Reading Low Quality Characters from Printouts},
   booktitle = {Proc. of 13th ICPR Vienna - Austria},
   month = {Aug},
   year = {1996},
   pages = {185--189},
   volume =3,
   abstract = {
In this paper a system is presented which is used to read low quality
machine-printed characters. It is used to read computer printouts when
the data file is not available. The assumptions on the characters are
that their font belongs to a set of known fonts and that they are
organized into tables or columns. Usually, the printer used for these
documents is fast and the printing quality is low, due to the used up
inked ribbon and to damaged nozzles or print head. Hence standard
machine-printed OCR systems feature about 15% error rate on these
sheets, a specific technique is needed. In order to cope with the
recognition of broken characters and character pieces, the system is
based on a two step strategy. First, it tries to match the unknown
character using a moving-window technique. Then, if this fails, it
creates a new reference image set using the already recognized
characters of the document and repeats the first matching step. Thus,
the correlation among damaged characters is used. The first step
allows to reach a 2% error rate and the application of the second step
lowers it to 0.15%. This low error rate is possible thanks to the
ability of the system to adapt its behavior to the damaged characters
produced by the printer. The average recognition time on a SUN
SparcStation 10 is 15ms/character, computed on about 100,000
characters contained in 50 documents.
},
}

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