Off-line cursive script word recognition
Bozinovic, R.M.
Srihari, S.N.
Dept. of Comput. Sci., State Univ. of New York, Buffalo, NY;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Jan 1989
Volume: 11,
Issue: 1
On page(s): 68-83
ISSN: 0162-8828
References Cited: 33
CODEN: ITPIDJ
INSPEC Accession Number: 3366826
Digital Object Identifier: 10.1109/34.23114
Current Version Published: 2002-08-06
Abstract
Cursive script word recognition is the problem of transforming a
word from the iconic form of cursive writing to its symbolic form.
Several component processes of a recognition system for isolated offline
cursive script words are described. A word image is transformed through
a hierarchy of representation levels: points, contours, features,
letters, and words. A unique feature representation is generated
bottom-up from the image using statistical dependences between letters
and features. Ratings for partially formed words are computed using a
stack algorithm and a lexicon represented as a trie. Several novel
techniques for low- and intermediate-level processing for cursive script
are described, including heuristics for reference line finding, letter
segmentation based on detecting local minima along the lower contour and
areas with low vertical profiles, simultaneous encoding of contours and
their topological relationships, extracting features, and finding
shape-oriented events. Experiments demonstrating the performance of the
system are also described
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