Multiview Rectification of Folded Documents
- Shaodi You ,
- Yasuyuki Matsushita ,
- Sudipta Sinha ,
- Yusuke Bou ,
- Katsushi Ikeuchi
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Digitally unwrapping images of paper sheets is crucial for accurate document scanning and text recognition. This paper presents a method for automatically rectifying curved or folded paper sheets from a few images captured from multiple viewpoints. Prior methods either need expensive 3D scanners or model deformable surfaces using over-simplified parametric representations. In contrast, our method uses regular images and is based on general developable surface models that can represent a wide variety of paper deformations. Our main contribution is a new robust rectification method based on ridge-aware 3D reconstruction of a paper sheet and unwrapping the reconstructed surface using properties of developable surfaces via ℓ1 conformal mapping. We present results on several examples including book pages, folded letters and shopping receipts.