2003 | OriginalPaper | Buchkapitel
Generation and Use of Synthetic Training Data in Cursive Handwriting Recognition
verfasst von : Muriel Helmers, Horst Bunke
Erschienen in: Pattern Recognition and Image Analysis
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Three different methods for the synthetic generation of handwritten text are introduced. These methods are experimentally evaluated in the context of a cursive handwriting recognition task, using an HMM-based recognizer. In the experiments, the performance of a traditional recognizer, which is trained on data produced by human writers, is compared to a system that is trained on synthetic data only. Under the most elaborate synthetic handwriting generation model, a level of performance comparable to, or even slightly better than, the system trained on the writing of humans was observed.