Abstract
In this paper we will present our investigations related to contextual modeling for HMM-based handwritten Arabic text recognition. We will, first, discuss the justifications and the need for contextual modeling for handwritten Arabic text recognition. Next, we will discuss the issues related to contextual modeling for Arabic text recognition. Finally, we will present our novel class-based contextual modeling for HMM-based handwritten Arabic text recognition. Experiment results on word recognition tasks show improvements in word recognition rates when compared to using standard contextual HMMs. Moreover, the recognizers are significantly more compact as compared to the standard contextual HMM systems.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2016 15th International Conference on Frontiers in Handwriting Recognition, ICFHR 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 554-559 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781509009817 |
| DOIs | |
| State | Published - 2 Jul 2016 |
Publication series
| Name | Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR |
|---|---|
| Volume | 0 |
| ISSN (Print) | 2167-6445 |
| ISSN (Electronic) | 2167-6453 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.
Keywords
- Arabic text recognition
- Class-based contextual modeling
- Contextutal modeling
- Handwritten text recognition
- Hidden Markov models
ASJC Scopus subject areas
- Computer Science Applications
- Computer Vision and Pattern Recognition