Abstract
This paper investigates the problem of the effectiveness of input quality on the performance evaluation of Arabic OCR systems. The experimental results show that performance for Arabic OCR systems gives accepted error rate for low noisy images and gives high error rate for images with high noises and Arabic OCR accuracy can be increased by filtering the noise images. Robust word-based and character-based accuracy metrics are used to show the performance evaluation of different Arabic OCR engines using different samples such as newspapers, books, regular text are used.
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Saber, S., Ahmed, A., Elsisi, A., Hadhoud, M. (2016). Performance Evaluation of Arabic Optical Character Recognition Engines for Noisy Inputs. In: Gaber, T., Hassanien, A., El-Bendary, N., Dey, N. (eds) The 1st International Conference on Advanced Intelligent System and Informatics (AISI2015), November 28-30, 2015, Beni Suef, Egypt. Advances in Intelligent Systems and Computing, vol 407. Springer, Cham. https://doi.org/10.1007/978-3-319-26690-9_40
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DOI: https://doi.org/10.1007/978-3-319-26690-9_40
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