A database for offline arabic handwritten text recognition

Authors:
Sabri A. Mahmoud;Irfan Ahmad;Mohammed Alshayeb;Wasfi G. Al-Khatib
Affiliations:
King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia;King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia;King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia;King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia
Venue:
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part II
Year:
2011

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Abstract

Arabic handwritten text recognition has not received the same attention as that directed towards Latin script-based languages. In this paper, we present our efforts to develop a comprehensive Arabic Handwritten Text database (AHTD). At this stage, the database will consist of text written by 1000 writers from different countries. Currently, it has data from over 300 writers. It is composed of an images database containing images of the written text at various resolutions, and a ground truth database that contains meta-data describing the written text at the page, paragraph, and line levels. Tools to extract paragraphs from pages, segment paragraphs into lines have also been developed. Segmentation of lines into words will follow. The database will be made freely available to researchers world-wide. It is hoped that the AHTD database will stir research efforts in various handwritten-related problems such as text recognition, and writer identification and verification.