Writer identification for historical arabic documents

Daniel Fecker, Abedelkadir Asit, Volker Märgner, Jihad El-Sana, Tim Fingscheidt

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

27 Scopus citations


Identification of writers of handwritten historical documents is an important and challenging task. In this paper we present several feature extraction and classification approaches for the identification of writers in historical Arabic manuscripts. The approaches are able to successfully identify writers of multipage documents. The feature extraction methods rely on different principles, such as contour-, textural- and key point-based and the classification schemes are based on averaging and voting. For all experiments a dedicated data set based on a publicly available database is used. The experiments show promising results and the best performance was achieved using a novel feature extraction based on key point descriptors.

Original languageEnglish
Title of host publicationProceedings - International Conference on Pattern Recognition
PublisherInstitute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781479952083
StatePublished - 4 Dec 2014
Event22nd International Conference on Pattern Recognition, ICPR 2014 - Stockholm, Sweden
Duration: 24 Aug 201428 Aug 2014

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651


Conference22nd International Conference on Pattern Recognition, ICPR 2014

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition


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