USING STROKE-BASED OR CHARACTER-BASED SELF-ORGANIZING MAPS IN THE RECOGNITION OF ONLINE, CONNECTED CURSIVE SCRIPT

L SCHOMAKER*

*Bijbehorende auteur voor dit werk

OnderzoeksoutputAcademicpeer review

35 Citaten (Scopus)

Samenvatting

Comparisons are made between a number of stroke-based and character-based recognizers of connected cursive script. In both approaches a Kohonen self-organizing neural network is used as a feature-vector quantizer. It is found that a ''best match only'' character-based recognizer performs better than a ''best match only'' stroke-based recognizer at the cost of a substantial increase in computation. However, allowing up to three multiple stroke interpretations yielded a much larger improvement on the performance of the stroke-based recognizer. Within the character-based architecture, a comparison is made between temporal and spatial resampling of characters. No significant differences between these resampling methods were found. Geometrical normalization (orientation, slant) did not significantly improve the recognition. Training sets of more than 500 cursive words appeared to be necessary to yield acceptable performance.

Originele taal-2English
Pagina's (van-tot)443-450
Aantal pagina's8
TijdschriftPattern recognition
Volume26
Nummer van het tijdschrift3
StatusPublished - mrt-1993

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