Voronoi++: A Dynamic Page Segmentation Approach Based on Voronoi and Docstrum Features

This paper presents a dynamic approach to document page segmentation. Current page segmentation algorithms lack the ability to dynamically adapt local variations in the size, orientation and distance of components within a page. Our approach builds upon one of the best algorithms, Kise et. al. work based on Area Voronoi Diagrams, which adapts globally to page content to determine algorithm parameters. In our approach, local thresholds are determined dynamically based on parabolic relations between components, and Docstrum based angular and neighborhood features are integrated to improve accuracy. Zone-based evaluation was performed on four sets of printed and handwritten documents in English and Arabic scripts and an increase of 33% in accuracy is reported.