doi: 10.7763/IJCTE.2013.V5.659
A Decision Tree Based Method to Classify Persian Handwritten Numerals by Extracting Some Simple Geometrical Features
Hamidreza Alvari
,
Seyed Mehdi Hazrati Fard ,
Bahar Salehi
- Shiraz University, Shiraz, Iran.
Abstract
Automatic recognition of handwritten numerals has been widely proposed in various languages. However, some languages such as Persian still need more consideration. In this paper, we proposed a handwritten Persian numerals dataset, which is gathered from people with different range of educational level. Thus, it is more general than other similar Persian datasets. Additionally, a method to classify Persian handwritten numerals is presented, which uses simple geometrical features based on their shapes, and classifies them via a rule-based decision tree classifier. Compared to other similar methods, our proposed method has the advantages of high speed running, employing too few and simple features, and elimination of training phase.
Keywords
- Decision tree
- feature extraction
- geometrical shape
- preprocess
How to Cite
Hamidreza Alvari, Seyed Mehdi Hazrati Fard, and Bahar Salehi, "A Decision Tree Based Method to Classify Persian Handwritten Numerals by Extracting Some Simple Geometrical Features," International Journal of Computer Theory and Engineering, vol. 5, no. 1, pp. 118-122, 2013. https://doi.org/10.7763/IJCTE.2013.V5.659
Copyright & License
Copyright © 2013 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).