@inproceedings{edf3ff4273264b9abca8c0ab7848b31c,
title = "Document Writer Analysis with Rejection for Historical Arabic Manuscripts",
abstract = "Determining the individuality of handwriting in ancient manuscripts is an important aspect of the manuscript analysis process. Automatic identification of writers in historical manuscripts can support historians to gain insights into manuscripts with missing metadata such as writer name, period, and origin. In this paper writer classification and retrieval approaches for multi-page documents in the context of historical manuscripts are presented. The main contribution is a learning-based rejection strategy which utilizes writer retrieval and support vector machines for rejecting a decision if no corresponding writer can be found for a query manuscript. Experiments using different feature extraction methods demonstrate the abilities of our proposed methods. A dedicated data set based on a publicly available database of historical Arabic manuscripts was used and the experiments show promising results.",
keywords = "decision rejection, historical manuscripts, writer identification",
author = "Daniel Fecker and Abedelkadir Asi and Werner Pantke and Volker M{\"a}rgner and Jihad El-Sana and Tim Fingscheidt",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014 ; Conference date: 01-09-2014 Through 04-09-2014",
year = "2014",
month = dec,
day = "9",
doi = "10.1109/ICFHR.2014.130",
language = "English",
series = "Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "743--748",
booktitle = "Proceedings - 14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014",
address = "United States",
}