A New Arabic Printed Text Image Database and Evaluation Protocols
Top Cited Papers
- 1 January 2009
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 946-950
- https://doi.org/10.1109/icdar.2009.155
Abstract
We report on the creation of a database composed of images of Arabic Printed words. The purpose of this database is the large-scale benchmarking of open-vocabulary, multi-font, multi-size and multi-style text recognition systems in Arabic. The challenges that are addressed by the database are in the variability of the sizes, fonts and style used to generate the images. A focus is also given on low-resolution images where anti-aliasing is generating noise on the characters to recognize. The database is synthetically generated using a lexicon of 113psila284 words, 10 Arabic fonts, 10 font sizes and 4 font styles. The database contains 45psila313psila600 single word images totaling to more than 250 million characters. Ground truth annotation is provided for each image. The database is called APTI for Arabic Printed Text Images.Keywords
This publication has 7 references indexed in Scilit:
- A New Arabic Printed Text Image Database and Evaluation ProtocolsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2009
- Duration Models for Arabic Text Recognition Using Hidden Markov ModelsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2008
- Offline recognition of omnifont Arabic text using the HMM ToolKit (HTK)Pattern Recognition Letters, 2007
- Affixal approach for Arabic decomposable vocabulary recognition a validation on printed word in only one fontPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- The architecture of a standard Arabic lexical databasePublished by Association for Computational Linguistics (ACL) ,2004
- Multi-font recognition of printed Arabic using the BBN BYBLOS speech recognition systemPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Statistical pattern recognition: a reviewIEEE Transactions on Pattern Analysis and Machine Intelligence, 2000