Comparison of global and cascading recognition systems applied to multi-font arabic text
Proceedings of the 10th ACM symposium on Document engineering
Pattern Recognition Letters
Offline arabic handwritten text recognition: A Survey
ACM Computing Surveys (CSUR)
Low resolution Arabic recognition with multidimensional recurrent neural networks
Proceedings of the 4th International Workshop on Multilingual OCR
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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 113’284 words, 10 Arabic fonts, 10 font sizes and 4 font styles. The database contains 45’313’600 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.