On-line handwritten formula recognition using statistical methods
Andreas Kosmala, Gerhard Rigoll · 2002
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 T/sub E/X-syntax in order to achieve a convenient visualization of the results.