doi: 10.7763/IJCTE.2012.V4.509
A Novel Approach to Segmentation of Persian Cursive Script Using Decision Tree
Shahriar Pirnia Naeini1
,
Maryam Khademi2 ,
Alireza Nikookar3
- 1Department of Computer Science, South Tehran Branch, Islamic Azad University, Tehran 11365/4435, Iran.
- 2Department of Applied Mathematics, South Tehran Branch, Islamic Azad University, Tehran 11365/4435, Iran.
- 3Young Researchers Club, South Tehran Branch, Islamic Azad University, Tehran 11365/4435, Iran.
Abstract
In this paper, we propose a novel method for segmentation of online Persian handwriting into the fundamental building blocks of Persian letters. Employing the findings of our previous work to determine the segmentation points of cursive words and applying some smoothing techniques to improve our results, we have advanced our model to form the pre-segments into the predefined building blocks (BBs) which will be used later for recognizing letters in written words. We have utilized a decision tree to accomplish this task and the 98.6% accuracy has been obtained in forming the BBs as the overall result.
Keywords
- Decision tree
- feature extraction
- online cursive script
- Persian words
- segmentation
How to Cite
Shahriar Pirnia Naeini, Maryam Khademi, and Alireza Nikookar, "A Novel Approach to Segmentation of Persian Cursive Script Using Decision Tree," International Journal of Computer Theory and Engineering, vol. 4, no. 3, pp. 465-467, 2012. https://doi.org/10.7763/IJCTE.2012.V4.509
Copyright & License
Copyright © 2012 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).