Removing Shadows from Images of Documents

Proceedings of ACCV 2016

     Steve Bako1          Soheil Darabi2          Eli Shechtman2     
        Jue Wang2         Kalyan Sunkavalli2        Pradeep Sen1         

1 University of California, Santa Barbara         2 Adobe         


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.

Paper and Additional Materials



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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