Validation of image defect models for optical character recognition
Yanhong Li
Lopresti, D.
Nagy, G.
Tomkins, A.
GARI Software, Livingston, NJ;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Feb 1996
Volume: 18,
Issue: 2
On page(s): 99-107
ISSN: 0162-8828
References Cited: 27
CODEN: ITPIDJ
INSPEC Accession Number: 5208602
Digital Object Identifier: 10.1109/34.481536
Current Version Published: 2002-08-06
Abstract
Considers the problem of evaluating character image generators
that model distortions encountered in optical character recognition
(OCR). While a number of such defect models have been proposed, the
contention that they produce the desired result is typically argued in
an ad hoc and informal way. The authors introduce a rigorous and more
pragmatic definition of when a model is accurate: they say a defect
model is validated if the OCR errors induced by the model are
indistinguishable from the errors encountered when using real scanned
documents. The authors describe four measures to quantify this
similarity, and compare and contrast them using over ten million scanned
and synthesized characters in three fonts. The measures differentiate
effectively between different fonts and different scans of the same font
regardless of the underlying text
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