Distinctive features in automatic recognition of handprinted characters
Identifieur interne : 000328 ( Istex/Curation ); précédent : 000327; suivant : 000329Distinctive features in automatic recognition of handprinted characters
Auteurs : Ching Y. Suen [Canada]Source :
- Signal Processing [ 0165-1684 ] ; 1981.
Abstract
Characters are recognized from the features extracted. Usually the input chacter is smoothed and cleaned by the preprocessor before it reaches the featuree extractor. Good preprocessors and feature extractors are the prerequisites to a successful character recognition system. Following a description of preprocessing techniques, the various features found in the vast accumulation of literature on handprint recognition are divided into two main categories: (1) global analysis, and (2) structural analysis. Further subdivision of these categories gives rise to six families of feature type, viz. (a) distribution of points, (b) transformation, (c) physical measurements, (d) line segments and edges, (e) outline of character, and (f) centre-line of character. Each family is described with illustrative examples. The performance and recognition rates of systems employing these features are discussed.
Url:
DOI: 10.1016/0165-1684(82)90021-4
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