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.;
