Muharaf: Manuscripts of Handwritten Arabic Dataset for Cursive Text Recognition

• URL: http://arxiv.org/abs/2406.09630v1
• Date: Thu, 13 Jun 2024 23:40:34 GMT
• Title: Muharaf: Manuscripts of Handwritten Arabic Dataset for Cursive Text Recognition
• Authors: Mehreen Saeed, Adrian Chan, Anupam Mijar, Joseph Moukarzel, Georges Habchi, Carlos Younes, Amin Elias, Chau-Wai Wong, Akram Khater,
• Abstract summary: The Manuscripts of Handwritten Arabic(Muharaf) dataset is a machine learning dataset consisting of more than 1,600 historic handwritten page images. This dataset was compiled to advance the state of the art in handwritten text recognition.
• Score: 5.28595286827031
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: We present the Manuscripts of Handwritten Arabic~(Muharaf) dataset, which is a machine learning dataset consisting of more than 1,600 historic handwritten page images transcribed by experts in archival Arabic. Each document image is accompanied by spatial polygonal coordinates of its text lines as well as basic page elements. This dataset was compiled to advance the state of the art in handwritten text recognition (HTR), not only for Arabic manuscripts but also for cursive text in general. The Muharaf dataset includes diverse handwriting styles and a wide range of document types, including personal letters, diaries, notes, poems, church records, and legal correspondences. In this paper, we describe the data acquisition pipeline, notable dataset features, and statistics. We also provide a preliminary baseline result achieved by training convolutional neural networks using this data.

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