Exploiting Vector Fields for Geometric Rectification of Distorted Document Images

Gaofeng Meng*, Yuanqi Su, Ying Wu, Shiming Xiang, Chunhong Pan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationComputer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings
EditorsYair Weiss, Vittorio Ferrari, Cristian Sminchisescu, Martial Hebert
PublisherSpringer Verlag
Number of pages16
ISBN (Print)9783030012694
StatePublished - 2018
Event15th European Conference on Computer Vision, ECCV 2018 - Munich, Germany
Duration: Sep 8 2018Sep 14 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11220 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other15th European Conference on Computer Vision, ECCV 2018


  • 3D shape recovery
  • Document image processing
  • Geometric rectification
  • OCR
  • Vector fields

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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