May 29th, 11 am
GEOCR: Good Enough OCR
Document Recognition Technologies, Inc.
Palo Alto, CA
OCR performs lexical post-processing to assist in the resolution
of errors produced in the upstream character recognition processes.
We change that model by incorporating lexical information very
early in recognition. The result is an OCR that has as its principal
attributes high speed of operation and tunability to the lexical
content of the documents to which it is applied. GEOCR relies
on the transformation of the text image into character shape codes,
a rapid and robust process, and on special lexica, indexed by
the "shapes" of words, containing the character ambiguities
present within particular word shape classifications. We rely
on the structure of language and the high percentage of singleton
mappings between the shape codes and the characters in the words.
Considerable ambiguity is removed by simple lookup in the specially
tuned and structured lexicon and substitution on a character-by-character
basis. Ambiguity is further reduced by template matching using
exemplars derived from surrounding text, taking advantage of the
local consistency of font, face and size as well as image quality.