Robust stereo correspondence for documents by matching connected components of text-lines with dynamic programming

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.