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ICDAR
2003
IEEE

Generation of Synthetic Training Data for an HMM-based Handwriting Recognition System

13 years 11 months ago
Generation of Synthetic Training Data for an HMM-based Handwriting Recognition System
A perturbation model for generating synthetic textlines from existing cursively handwritten lines of text produced by human writers is presented. Our purpose is to improve the performance of an HMM-based off-line cursive handwriting recognition system by providing it with additional synthetic training data. Two kinds of perturbations are applied, geometrical transformations and thinning/thickening operations. The proposed perturbation model is evaluated under different experimental conditions.
Tamás Varga, Horst Bunke
Added 04 Jul 2010
Updated 04 Jul 2010
Type Conference
Year 2003
Where ICDAR
Authors Tamás Varga, Horst Bunke
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