The Common Fold: Utilizing the Four-Fold to Dewarp Printed Documents from a Single Image

Abstract

Handheld cameras are currently the device of choice for performing document digitization, due to their convenience, ubiquity and high performance at low cost. Software methods process a captured image, to rectify distortions and reconstruct the original document. Existing methods struggle to reconstruct a flattened version given a single image of a document distorted by folding. We propose a novel non-parametric page dewarping approach from a single image based on deep learning to identify creases due to folds on the paper. Our method then performs a 2D boundary method based on polynomial regression, and a Coons patch, to get a flattened reconstruction. We found our method improves OCR word accuracy by more than 2.5 times when compared to the original distorted image.