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AlexU-Word: A New Dataset for Isolated-Word Closed-Vocabulary Offline Arabic Handwriting Recognition

arXiv · · Notable

NLP Arabic AI Research Dataset CV

Summary

Researchers from Alexandria University introduce AlexU-Word, a new dataset for offline Arabic handwriting recognition. The dataset contains 25,114 samples of 109 unique Arabic words, covering all letter shapes, collected from 907 writers. The dataset is designed for closed-vocabulary word recognition and to support segmented letter recognition-based systems. Why it matters: This dataset can help advance Arabic handwriting recognition systems, addressing a need for high-quality Arabic datasets in NLP research.

Keywords

Arabic handwriting recognition · dataset · AlexU-Word · NLP · Alexandria University

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Window-Based Descriptors for Arabic Handwritten Alphabet Recognition: A Comparative Study on a Novel Dataset

arXiv ·

This paper introduces a novel dataset for Arabic handwritten isolated alphabet letters to serve as a benchmark for future research. The study presents a comparative evaluation of window-based descriptors for Arabic handwritten alphabet recognition, testing different descriptors with various classifiers. The experiments demonstrate that window-based descriptors perform well, especially when combined with a novel spatial pyramid partitioning scheme. Why it matters: The new dataset and analysis of descriptors will help advance Arabic OCR and handwritten text recognition systems.