Title :
Automatic Feature Design for Optical Character Recognition Using an Evolutionary Search Procedure
Author :
Stentiford, Fred W. M.
Author_Institution :
British Telecom Research Laboratories. Ipswich, Suffolk, England.
fDate :
5/1/1985 12:00:00 AM
Abstract :
An automatic evolutionary search is applied to the problem of feature extraction in an OCR application. A performance measure based on feature independence is used to generate features which do not appear to suffer from peaking effects [17]. Features are extracted from a training set of 30 600 machine printed 34 class alphanumeric characters derived from British mail. Classification results on the training set and a test set of 10 200 characters are reported for an increasing number of features. A 1.01 percent forced decision error rate is obtained on the test data using 316 features. The hardware implementation should be cheap and fast to operate. The performance compares favorably with current low cost OCR page readers.
Keywords :
Character recognition; Costs; Error analysis; Feature extraction; Hardware; Optical character recognition software; Optical design; Pattern recognition; Postal services; Testing; Evolution; feature extraction; image processing; nearest neighbor classifier; optical character; pattern recognition;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1985.4767665