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Diagnosis of Mathematical Symbols using Hidden Markov Model
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 125 - Number 1 |
| Year of Publication: 2015 |
| Authors: Mohamad Hassan Asadi, Abbas Akkasi, Ebrahim Zargarpour, Zahra Mohammdi |
10.5120/ijca2015905711
|
Mohamad Hassan Asadi, Abbas Akkasi, Ebrahim Zargarpour, Zahra Mohammdi . Diagnosis of Mathematical Symbols using Hidden Markov Model. International Journal of Computer Applications. 125, 1 ( September 2015), 40-42. DOI=10.5120/ijca2015905711
Abstract
Diagnosis of mathematical symbols in handwritings is originated from Optical Character Recognition (OCR) method. Recognition of mathematical symbols increases the accuracy of calculations. In present study, hidden Markov model is applied with a new feature selection system. Considering previous studies, a lot of researches performed on mathematical symbols recognition, have used support vector machine. Test process in this method is time-consuming and it is not advised to use it. In this new approach, the result is 96.05% accuracy for Infity database and 96% for IRISA database.
References
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