Character recognition without segmentation
Rocha, J.
Pavlidis, T.
Dept. de Math. Inf., Univ. de les Illes Balears, Palma de Mallorca;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Sep 1995
Volume: 17,
Issue: 9
On page(s): 903-909
ISSN: 0162-8828
References Cited: 23
CODEN: ITPIDJ
INSPEC Accession Number: 5068825
Digital Object Identifier: 10.1109/34.406657
Current Version Published: 2002-08-06
Abstract
A segmentation-free approach to OCR is presented as part of a
knowledge-based word interpretation model. It is based on the
recognition of subgraphs homeomorphic to previously defined prototypes
of characters. Gaps are identified as potential parts of characters by
implementing a variant of the notion of relative neighborhood used in
computational perception. Each subgraph of strokes that matches a
previously defined character prototype is recognized anywhere in the
word even if it corresponds to a broken character or to a character
touching another one. The characters are detected in the order defined
by the matching quality. Each subgraph that is recognized is introduced
as a node in a directed net that compiles different alternatives of
interpretation of the features in the feature graph. A path in the net
represents a consistent succession of characters. A final search for the
optimal path under certain criteria gives the best interpretation of the
word features. Broken characters are recognized by looking for gaps
between features that may be interpreted as part of a character.
Touching characters are recognized because the matching allows
nonmatched adjacent strokes. The recognition results for over 24,000
printed numeral characters belonging to a USPS database and on some
hand-printed words confirmed the method's high robustness level
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