REPORT camvin00/IDIAP Cursive Character Recognition by Learning Vector Quantization Camastra, Francesco Vinciarelli, Alessandro EXTERNAL http://publications.idiap.ch/attachments/reports/2000/rr00-47.pdf PUBLIC Idiap-RR-47-2000 2000 IDIAP Accepted for publication by Pattern Recognition Letters 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.