TU Dortmund Department of Computer Science LS XII Pattern Recognition GroupPublications → Publication Details

On Appearance-Based Feature Extraction Methods for Writer-Independent Handwritten Text Recognition

G. A. Fink and T. Pl{\"o}tz
Proc. Int. Conf. on Document Analysis and Recognition, pages 1070-1074, Seoul, Korea, 2005.

Most successful systems for the recognition of unconstrained handwriting currently rely on expert-crafted feature sets that compute local geometric properties from text images. However, by applying appearance based analysis techniques appropriate features could be derived from training data automatically. Therefore, in this paper several different methods for computing appearance based feature representations were investigated and compared to the performance of a state-of-the-art writer-independent recognition system based on geometric features. In extensive experiments promising results were obtained on a challenging recognition task

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