MergeLayouts-overcoming faulty segmentations by a comprehensive voting of commercial OCR devices

Abstract

In this paper we present a comprehensive voting approach, taking entire layouts obtained from commercial OCR devices as input. Such a layout comprises segments of three kinds: lines, words, and characters. By combining all attributes of a segment (e.g. recognized text, font height etc.), we attain a "better" layout, representing the original page layout as good as possible. The voting process itself is hierarchically organized, starting with the line segments. For each level, a search tree is spawn and all fellow segments (segments front different layouts which denote the same image area) are established. A heuristic search method is utilized which is guided by a similarity measure defined on segments. Deviations in the segmentation, as well as segmentation errors of individual commercial OCR devices, are compensated by an "equalization module".