Abstract
Font recognition is useful for improving optical text recognition systems' accuracy and time, and to restore the documents' original formats. This paper addresses a need for Arabic font recognition research by introducing an Arabic font recognition database consisting of 40 fonts, 10 sizes (ranging from 8 to 24 points) and 4 styles (viz. normal, bold, italic, and bold-italic). The database is split into three sets (viz. training, validation, and testing). The database is freely available to researchers.1 Moreover, we introduce a baseline font recognition system for benchmarking purposes, and report identification rates on our KAFD database and the Arabic Printed Text Image (APTI) database with 20 and 10 fonts, respectively. The best recognition rates are achieved using log-Gabor filters.
| Original language | English |
|---|---|
| Pages (from-to) | 2231-2240 |
| Number of pages | 10 |
| Journal | Pattern Recognition |
| Volume | 47 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 2014 |
Bibliographical note
Funding Information:The authors would like to acknowledge the support provided by King Abdul-Aziz City for Science and Technology (KACST) for funding this work under Project no. AT-30–53 through King Fahd University of Petroleum & Minerals (KFUPM). The third author would like to thank Qassim University for supporting this research and providing the computing facilities. The authors would also like to thank the anonymous reviewers whose comments helped in improving this paper.
Keywords
- Arabic font database
- Arabic font recognition
- Classification
- Feature extraction
- Log-Gabor filters
ASJC Scopus subject areas
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence