Abstract
In this work, we automatically detect and remove distracting shadows from photographs of documents and other text-based items. Documents typically have a constant colored background; based on this observation, we propose a technique to estimate background and text color in local image blocks. We match these local background color estimates to a global reference to generate a \textit{shadow map}. Correcting the image with this shadow map produces the final unshadowed output. We demonstrate that our algorithm is robust and produces high-quality results, qualitatively and quantitatively, in both controlled and real-world settings containing large regions of significant shadow.
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Bibtex
@article{Bako16, author = {Steve Bako and Soheil Darabi and Eli Shechtman and Jue Wang and Kalyan Sunkavalli and Pradeep Sen},
title = {Removing Shadows from Images of Documents}, journal = {Asian Conference on Computer Vision (ACCV 2016)},
year = {2016}, }
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