Title :
On-line handwritten formula recognition using statistical methods
Author :
Kosmala, Andreas ; Rigoll, Gerhard
Author_Institution :
Fac. of Electr. Eng., Gerhard-Mercator-Univ., Duisburg, Germany
Abstract :
This paper presents the design of a system for the processing and recognition of online handwritten mathematical formulas. The hidden Markov model (HMM) based system is trained and evaluated with a writer dependent database consisting of 100 formulas for the training and an additional set of 30 formulas for the test. With the introduction of some constraints, it is possible to obtain high recognition rates up to 97.7%, and to transform the transcriptions of the formulas into TE X-syntax in order to achieve a convenient visualization of the results
Keywords :
character sets; handwritten character recognition; statistical analysis; HMM-based system; TEX-syntax; hidden Markov model; online handwritten mathematical formulas; statistical methods; writer dependent database; Communication channels; Computer science; Handwriting recognition; Hidden Markov models; Humans; Man machine systems; Speech recognition; Statistical analysis; System testing; Writing;
Conference_Titel :
Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
Conference_Location :
Brisbane, Qld.
Print_ISBN :
0-8186-8512-3
DOI :
10.1109/ICPR.1998.711941
