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Computer Vision, IEEE International Conference on (2005)
Beijing, China
Oct. 17, 2005 to Oct. 20, 2005
ISSN: 1550-5499
ISBN: 0-7695-2334-X
pp: 1117-1123
Yun Lin , University of Kentucky
George Landon , University of Kentucky
Mingxuan Sun , University of Kentucky
Brent Seales , University of Kentucky
Michael S. Brown , Nanyang Technological University
Ruigang Yang , University of Kentucky
We present a system to restore the 2D content printed on distorted documents. Our system works by acquiring a 3D scan of the document?s surface together with a high-resolution image. Using the 3D surface information and the 2D image, we can ameliorate unwanted surface distortion and effects from non-uniform illumination. Our system can process arbitrary geometric distortions, not requiring any pre-assumed parametric models for the document?s geometry. The illumination correction uses the 3D shape to distinguish content edges from illumination edges to recover the 2D content?s reflectance image while making no assumptions about light sources and their positions. Results are shown for real objects, demonstrating a complete framework capable of restoring geometric and photometric artifacts on distorted documents.
Yun Lin, George Landon, Mingxuan Sun, Brent Seales, Michael S. Brown, Ruigang Yang, "Geometric and Photometric Restoration of Distorted Documents", Computer Vision, IEEE International Conference on, vol. 02, no. , pp. 1117-1123, 2005, doi:10.1109/ICCV.2005.106
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