On writer identification for Arabic historical manuscripts

被引:0
作者
Abedelkadir Asi
Alaa Abdalhaleem
Daniel Fecker
Volker Märgner
Jihad El-Sana
机构
[1] Ben-Gurion University of the Negev,Department of Computer Science
[2] Technische Universität Braunschweig,Institute for Communications Technology
来源
International Journal on Document Analysis and Recognition (IJDAR) | 2017年 / 20卷
关键词
Writer identification; Writer retrieval; Key point-based features; Contour-based features; Supervised learning; Hierarchical clustering; Classification;
D O I
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中图分类号
学科分类号
摘要
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.
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页码:173 / 187
页数:14
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