Removing shadows from images of documents

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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 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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Bako, S., Darabi, S., Shechtman, E., Wang, J., Sunkavalli, K., & Sen, P. (2017). Removing shadows from images of documents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10113 LNCS, pp. 173–183). Springer Verlag. https://doi.org/10.1007/978-3-319-54187-7_12

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