An Arabic handwriting synthesis system
نویسندگان
چکیده
In this paper, we present an Arabic handwriting synthesis system. Two concatenation models to synthesize Arabic words from segmented characters are adopted: Extended-Glyphs connection and Synthetic-Extensions connection. We use our system to synthesize handwriting from a collected dataset and inject it into an expanded dataset. We experiment by training a state-of-the-art Arabic handwriting recognition system on the collected dataset, as well as on the expanded dataset, and test it on the IFN/ ENIT Arabic benchmark dataset. We show significant improvement in recognition performance due to the data that was synthesized by our system. & 2014 Elsevier Ltd. All rights reserved.
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عنوان ژورنال:
- Pattern Recognition
دوره 48 شماره
صفحات -
تاریخ انتشار 2015