Robust Stereo Correspondence for Documents by Matching Connected Components of Text-Lines with Dynamic Programming

Martin Krämer, Muhammad Zeshan Afzal, Syed Saqib Bukhari, Faisal Shafait, Thomas Breuel

In: 21st International Conference on Pattern Recognition. International Conference on Pattern Recognition (ICPR-2012) November 11-15 Tsukuba Science City Japan IEEE 2012.


In this paper we present a novel method for robust stereo matching on document image pairs. The matching itself is performed using an affine-invariant similarity measurement to compensate for perspective distortions, where affine invariance is achieved by normalization using second-order statistics, to finally allow a simple pixel-wise comparison. To handle the inherent high self-similarity of the page content we apply a dynamic programming approach on text-line pairs. We quantitatively show that the proposed method performs better in comparison to standard approaches using SURF - whether with or without incorporating text-line information.

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz