A soft-decision approach for symbol segmentation within handwritten mathematical expressions

Authors:
S. Lehmberg;H.-J. Winkler;M. Lang
Affiliations:
Inst. for Human-Machine-Commun., Tech. Univ. Munchen, Germany;-;-
Venue:
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 06
Year:
1996

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A global learning approach for an online handwritten mathematical expression recognition system

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Abstract

A soft-decision approach for symbol segmentation within on-line sampled handwritten mathematical expressions is presented. Based on stroke-specific features as well as geometrical features between the strokes a symbol hypotheses net is generated. For assistance additional knowledge obtained by a symbol prerecognition stage is used. The results achieved by the segmentation and prerecognition experiments indicate the performance of our approach.