Paper Info
Title
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.
Year
DOI
Venue
2017
10.1145/3103010.3121030
DocEng
Keywords
Field
DocType
Folded Document Dewarping, Document Reconstruction, Document Image Processing
Computer vision,Digitization,Computer science,Polynomial regression,Image based,Coons patch,Software,Mobile device,Artificial intelligence,Deep learning,Word accuracy
Conference
ISBN
Citations 
PageRank 
978-1-4503-4689-4
2
0.37
References 
Authors
13
4
Name
Order
Citations
PageRank
Sagnik Das142.44
Gaurav Mishra220.37
Akshay Sudharshana320.37
Roy Shilkrot416114.81