Loading...
research article
Cursive Character Recognition by Learning Vector Quantization
This paper presents a cursive character recognizer embedded in an off-line cursive script recognition system. The recognizer is composed of two modules: the first one is a feature extractor, the second one an LVQ. The selected feature set was compared to Zernike polynomials using the same classifier. Experiments are reported on a database of about 49000 isolated characters.
Loading...
Name
rr00-47.pdf
Access type
openaccess
Size
247.85 KB
Format
Adobe PDF
Checksum (MD5)
eb68c90ef8e4f0441a68b14010ce077a