A shape analysis model with applications to a character recognitionsystem
Rocha, J.
Pavlidis, T.
Dept. of Comput. Sci., State Univ. of New York, Stony Brook, NY;
This paper appears in: Applications of Computer Vision, Proceedings, 1992., IEEE Workshop on
Publication Date: 30 Nov-2 Dec 1992
On page(s): 182-189
Meeting Date: 11/30/1992 - 12/02/1992
Location: Palm Springs, CA, USA
ISBN: 0-8186-2840-5
References Cited: 17
INSPEC Accession Number: 4450915
Digital Object Identifier: 10.1109/ACV.1992.240313
Current Version Published: 2002-08-06
Abstract
A method for the recognition of multifont printed characters is
proposed, giving emphasis to the identification of structural
descriptions of character shapes using prototypes. Noise and shape
variations are modeled as series of transformations from groups of
features in the data to features in each prototype. Thus, the method
manages systematically the relative distortion between a candidate shape
and its prototype, accomplishing robustness to noise with less than two
prototypes per class, on the average. Our method uses a flexible
matching between components and a flexible grouping of the individual
components to be matched. A number of shape transformations are defined.
Also, a measure of the amount of distortion that these transformations
cause is given. The problem of classification of character shapes is
defined as a problem of optimization among the possible transformations
that map an input shape into prototypical shapes. Some tests with hand
printed numerals confirmed the method's high robustness level
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