גהאד אלצאנע

אקדמי בכיר

On writer identification for Arabic historical manuscripts

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

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.

שפת פרסום אנגלית
דפים 173-187
כתב עת International Journal on Document Analysis and Recognition
כרך 20
נושא מספר 3
סטטוס פרסום פורסם - 01.09.2017

Keywords

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

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Computer Science Applications
גישה למסמך
10.1007/s10032-017-0289-3
קבצים וקישורים אחרים
Link to publication in Scopus