Morphological degradation models and their use in document imagerestoration
Qigong Zheng
Kanungo, T.
Center for Autom. Res., Maryland Univ., College Park, MD;
This paper appears in: Image Processing, 2001. Proceedings. 2001 International Conference on
Publication Date: 2001
Volume: 1,
On page(s): 193-196 vol.1
Meeting Date: 10/07/2001 - 10/10/2001
Location: Thessaloniki, Greece
ISBN: 0-7803-6725-1
References Cited: 8
INSPEC Accession Number: 7210841
Digital Object Identifier: 10.1109/ICIP.2001.958986
Current Version Published: 2002-08-07
Abstract
Document images undergo various degradation processes. Numerous
models of these degradation processes have been proposed in the
literature. In this paper we propose a model-based restoration
algorithm. The restoration algorithm first estimates the parameters of a
degradation model and then uses the estimated parameters to construct a
lookup table for restoring the degraded image. The estimated degradation
model is used to estimate the probability of an ideal binary pattern,
given the noisy observed pattern. This probability is estimated by
degrading noise-free document images and then computing the frequency of
corresponding noise-free and noisy pattern pairs. This conditional
probability is then used to construct a lookup table to restore noisy
images. The impact of the restoration process is then quantified by
computing the decrease in OCR word and character error rate. We find
that given the estimated degradation model parameter values, the
restoration algorithm decreases the character error rate by 16.1% and
the word error rate by 7.35%. In some categories of degradation (e.g.
model parameters that give rise to broken characters) there is a 41.5%
reduction in character error rate and 20.4% reduction in word error rate
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