
Performance evaluation of Optical Character Recognition (OCR) systems is an essential task for OCR systems development. However, studies in Arabic OCR suffer from the lack of proper performance evaluation metrics and the availability of evaluation tools. Although the literature provides typical performance metrics, such as character accuracy and word accuracy for OCR performance evaluation, these metrics are not sufficient for evaluating Arabic OCR. This paper presents an open source automated software tool with various metrics for the evaluation of Arabic OCR performance. The developed tool is available for OCR researchers, thus it can be applied for ranking different OCR algorithms.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
