Algorithms for Recognizing Contour-Traced Handprinted Characters

Author

Toussaint, Godfried T. ; Donaldson, Robert W.

Issue

6

fYear

1970

fDate

6/1/1970 12:00:00 AM

Firstpage

541

Lastpage

546

Abstract

A contour-tracing technique originally devised by Clemens and Mason was modified and used with several different classifiers to recognize upper case handprinted characters. Recognition accuracies obtained compare favorably with other published results, particularly when additional simple tests are performed to differentiate commonly confused characters. One suboptimum classifier, in addition to yielding near optimum performance when tested on training data, uses much less statistical information than the optimum Bayes classifier and is significantly better than the optimum classifier when training and test data are limited.

Keywords

Character recognition, classification algorithms, contextual constraints, contour analysis, decision trees, feature extraction, handprinted characters, limited-data experiments, machine learning, suboptimum classification.; Algorithm design and analysis; Character recognition; Classification algorithms; Classification tree analysis; Decoding; Feature extraction; Machine learning algorithms; Performance evaluation; Testing; Training data; Character recognition, classification algorithms, contextual constraints, contour analysis, decision trees, feature extraction, handprinted characters, limited-data experiments, machine learning, suboptimum classification.;

fLanguage

English

Journal_Title

Computers, IEEE Transactions on

Publisher

ieee

ISSN

0018-9340

Type

jour

DOI

10.1109/T-C.1970.222972

Filename

1671565