On writer identification for Arabic historical manuscripts

Abedelkadir Asi, Alaa Abdalhaleem, Daniel Fecker, Volker Märgner, Jihad El-Sana

Research output: Contribution to journalArticlepeer-review


This paper introduces new methodologies for reliably identifying writers of Arabic historical manuscripts. We propose an approach that transforms key point-based features, such as SIFT, into a global form that captures high-level characteristics of writing styles. We suggest a modification for a common local feature, the contour direction feature, and show the contribution of combining local and global features for writer identification. Our work also presents a novel algorithm that determines the number of writers involved in writing a given manuscript. The experimental study confirms the significant improvement in this algorithm on writer identification once applied to historical manuscripts. Comprehensive experiments using different features and classification schemes demonstrate the vitality of the suggested methodologies for reliable writer identification. The presented techniques were evaluated on both historical and modern documents where the suggested features yielded very promising results with respect to state-of-the-art features.

Original languageAmerican English
Pages (from-to)173-187
Number of pages15
JournalInternational Journal on Document Analysis and Recognition
Issue number3
StatePublished - 1 Sep 2017


  • Classification
  • Contour-based features
  • Hierarchical clustering
  • Key point-based features
  • Supervised learning
  • Writer identification
  • Writer retrieval

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications


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