KHATT: Arabic offline Handwritten Text Database

Sabri A. Mahmoud*, Irfan Ahmad, Mohammad Alshayeb, Wasfi G. Al-Khatib, Mohammad Tanvir Parvez, Gernot A. Fink, Volker Märgner, Haikal El Abed

*Corresponding author for this work

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

98 Scopus citations

Abstract

In this paper, we report our comprehensive Arabic offline Handwritten Text database (KHATT) after completion of the collection of 1000 handwritten forms written by 1000 writers from different countries. It is composed of an image database containing images of the written text at 200, 300, and 600 dpi resolutions, a manually verified ground truth database that contains meta-data describing the written text at the page, paragraph, and line levels. A formal verification procedure is implemented to align the handwritten text with its ground truth at the form, paragraph and line levels. Tools to extract paragraphs from pages and segment paragraphs into lines are developed. Preliminary experiments on Arabic handwritten text recognition are conducted using sample data from the database and the results are reported. The database will be made freely available to researchers world-wide for research in various handwritten-related problems such as text recognition, writer identification and verification, etc.

Original languageEnglish
Title of host publicationProceedings - 13th International Conference on Frontiers in Handwriting Recognition, ICFHR 2012
Pages449-454
Number of pages6
DOIs
StatePublished - 2012

Publication series

NameProceedings - International Workshop on Frontiers in Handwriting Recognition, IWFHR
ISSN (Print)1550-5235

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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