On-line handwritten formula recognition with integrated correction recognition and execution

Andreas Kosmala, Gerhard Rigoll, Anja Brakensiek

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

This paper presents the extension of an approach for online handwritten formula recognition. The introduction of some constraints concerning the handwriting production process and the robust Hidden Markov Model (HMM) framework yields recognition rates up to 97.7 %. The high, but still limited recognition rate demonstrates the user's need for some correction facilities, in order to modify misclassified symbols and thus to avoid the re-writing of the entire expression. Such facilities can further be used to provide the opportunity to develop an expression on the electronic paper, as it is often desired from a practical point of view.

Original languageEnglish
Pages (from-to)590-593
Number of pages4
JournalProceedings - International Conference on Pattern Recognition
Volume15
Issue number2
StatePublished - 2000
Externally publishedYes

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