A database for offline Arabic handwritten text recognition

Sabri A. Mahmoud*, Irfan Ahmad, Mohammed Alshayeb, Wasfi G. Al-Khatib

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

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.

Original languageEnglish
Title of host publicationImage Analysis and Recognition - 8th International Conference, ICIAR 2011, Proceedings
Pages397-406
Number of pages10
EditionPART 2
DOIs
StatePublished - 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6754 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Arabic Handwritten Text Database
  • Arabic OCR
  • Document Analysis
  • Form Processing

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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