W-TSV: Weighted topological signature vector for lexicon reduction in handwritten Arabic documents

This paper proposes a holistic lexicon-reduction method for ancient and modern handwritten Arabic documents. The word shape is represented by the weighted topological signature vector (W-TSV), which encodes graph data into a low-dimensional vector space. Three directed acyclic graph (DAG) representations are proposed for Arabic word shapes, based on topological and geometrical features. Lexicon reduction is achieved by a nearest neighbors search in the W-TSV space. The proposed framework has been tested on the IFN/ENIT and the Ibn Sina databases, achieving respectively a degree of reduction of 83.5% and 92.9% for an accuracy of reduction of 90%.

► A shape-based approach for lexicon reduction of Arabic documents is introduced. ► The topological signature vector formulation is extended to weighted graphs. ► Three graphical representations for Arabic word shape are proposed. ► Experiments were performed on the IFN/ENIT and Ibn Sina databases. ► Topological and geometrical information of word shapes improves the performance.