Comparison of Global and Cascading Recognition Systems Applied to Multi-font Arabic Text
| Type of publication: | Inproceedings |
| Citation: | |
| Booktitle: | 10th ACM Symposium on Document Engineering (DocEng2010) |
| Year: | 2010 |
| Month: | September |
| Pages: | 161-164 |
| Location: | Manchester (United Kingdom) |
| DOI: | 10.1145/1860559.1860591 |
| Abstract: | A known difficulty of Arabic text recognition is in the large variability of printed representation from one font to the other. In this paper, we present a comparative study be- tween two strategies for the recognition of multi-font Arabic text. The first strategy is to use a global recognition system working independently on all the fonts. The second strategy is to use a so-called cascade built from a font identification system followed by font-dependent systems. In order to reach a fair comparison, the feature extraction and the modeling algorithms based on HMMs are kept as similar as possible between both approaches. The evaluation is carried out on the large and publicly available APTI (Arabic Printed Text Image) database with 10 different fonts. The results are showing a clear advantage of performance for the cascading approach. However, the cascading system is more costly in terms of cpu and memory. |
| Keywords: | arabic, HMM, image processing, machine learning, OCR |
| Authors | |
| Added by: | [] |
| Total mark: | 0 |
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