TY - GEN
T1 - Exploiting Vector Fields for Geometric Rectification of Distorted Document Images
AU - Meng, Gaofeng
AU - Su, Yuanqi
AU - Wu, Ying
AU - Xiang, Shiming
AU - Pan, Chunhong
N1 - Funding Information:
We thank the kind area chair and the anonymous reviewers for their valuable comments. This work was supported in part by the National Natural Science Foundation of China under Grants 91646207, National Science Foundation grant IIS-1217302, IIS-1619078, and the Army Research OfficeAROW911NF-16-1-0138.
Funding Information:
Acknowledgment. We thank the kind area chair and the anonymous reviewers for their valuable comments. This work was supported in part by the National Natural Science Foundation of China under Grants 91646207, National Science Foundation grant IIS-1217302, IIS-1619078, and the Army Research Office ARO W911NF-16-1-0138.
Publisher Copyright:
© 2018, Springer Nature Switzerland AG.
PY - 2018
Y1 - 2018
N2 - This paper proposes a segment-free method for geometric rectification of a distorted document image captured by a hand-held camera. The method can recover the 3D page shape by exploiting the intrinsic vector fields of the image. Based on the assumption that the curled page shape is a general cylindrical surface, we estimate the parameters related to the camera and the 3D shape model through weighted majority voting on the vector fields. Then the spatial directrix of the surface is recovered by solving an ordinary differential equation (ODE) through the Euler method. Finally, the geometric distortions in images can be rectified by flattening the estimated 3D page surface onto a plane. Our method can exploit diverse types of visual cues available in a distorted document image to estimate its vector fields for 3D page shape recovery. In comparison to the state-of-the-art methods, the great advantage is that it is a segment-free method and does not have to extract curved text lines or textual blocks, which is still a very challenging problem especially for a distorted document image. Our method can therefore be freely applied to document images with extremely complicated page layouts and severe image quality degradation. Extensive experiments are implemented to demonstrate the effectiveness of the proposed method.
AB - This paper proposes a segment-free method for geometric rectification of a distorted document image captured by a hand-held camera. The method can recover the 3D page shape by exploiting the intrinsic vector fields of the image. Based on the assumption that the curled page shape is a general cylindrical surface, we estimate the parameters related to the camera and the 3D shape model through weighted majority voting on the vector fields. Then the spatial directrix of the surface is recovered by solving an ordinary differential equation (ODE) through the Euler method. Finally, the geometric distortions in images can be rectified by flattening the estimated 3D page surface onto a plane. Our method can exploit diverse types of visual cues available in a distorted document image to estimate its vector fields for 3D page shape recovery. In comparison to the state-of-the-art methods, the great advantage is that it is a segment-free method and does not have to extract curved text lines or textual blocks, which is still a very challenging problem especially for a distorted document image. Our method can therefore be freely applied to document images with extremely complicated page layouts and severe image quality degradation. Extensive experiments are implemented to demonstrate the effectiveness of the proposed method.
KW - 3D shape recovery
KW - Document image processing
KW - Geometric rectification
KW - OCR
KW - Vector fields
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U2 - 10.1007/978-3-030-01270-0_11
DO - 10.1007/978-3-030-01270-0_11
M3 - Conference contribution
AN - SCOPUS:85055121371
SN - 9783030012694
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 180
EP - 195
BT - Computer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings
A2 - Weiss, Yair
A2 - Ferrari, Vittorio
A2 - Sminchisescu, Cristian
A2 - Hebert, Martial
PB - Springer Verlag
T2 - 15th European Conference on Computer Vision, ECCV 2018
Y2 - 8 September 2018 through 14 September 2018
ER -