Title :
A soft-decision approach for symbol segmentation within handwritten mathematical expressions
Author :
Lehmberg, Stefan ; Winkler, Hans-Jìrgen ; Lang, Manfred
Author_Institution :
Inst. for Human-Machine-Commun., Tech. Univ. Munchen, Germany
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
Keywords :
character recognition; feature extraction; handwriting recognition; image recognition; image sampling; image segmentation; neural nets; geometrical features; neural networks; online sampled handwritten mathematical expressions; performance; prerecognition experiments; segmentation experiments; soft-decision approach; stroke specific features; symbol hypotheses net; symbol prerecognition; symbol segmentation; Handwriting recognition; Image segmentation; Text recognition; Writing;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-3192-3
DOI :
10.1109/ICASSP.1996.550766
