Publication | Closed Access
The Common Fold
29
Citations
24
References
2017
Year
Unknown Venue
EngineeringMachine LearningGeometryDeblurringImage AnalysisKnot TheoryPattern RecognitionText RecognitionHandheld CamerasDocument DigitizationDigital RestorationComputational ImagingOptical Character RecognitionEnumerative GeometryDeep LearningComputer VisionHumanitiesFlattened ReconstructionCommon FoldDocument Processing
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.
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