CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 2012 vol.34 Issue No.04 - April

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Issue No.04 - April (2012 vol.34)

pp: 707-722

Gaofeng Meng , Chinese Academy of Sciences, Beijing

Chunhong Pan , Chinese Academy of Sciences, Beijing

Shiming Xiang , Chinese Academy of Sciences , Beijing

Jiangyong Duan , Chinese Academy of Sciences, Beijing

ABSTRACT

In this paper, we propose a metric rectification method to restore an image from a single camera-captured document image. The core idea is to construct an isometric image mesh by exploiting the geometry of page surface and camera. Our method uses a general cylindrical surface (GCS) to model the curved page shape. Under a few proper assumptions, the printed horizontal text lines are shown to be line convergent symmetric. This property is then used to constrain the estimation of various model parameters under perspective projection. We also introduce a paraperspective projection to approximate the nonlinear perspective projection. A set of close-form formulas is thus derived for the estimate of GCS directrix and document aspect ratio. Our method provides a straightforward framework for image metric rectification. It is insensitive to camera positions, viewing angles, and the shapes of document pages. To evaluate the proposed method, we implemented comprehensive experiments on both synthetic and real-captured images. The results demonstrate the efficiency of our method. We also carried out a comparative experiment on the public CBDAR2007 data set. The experimental results show that our method outperforms the state-of-the-art methods in terms of OCR accuracy and rectification errors.

INDEX TERMS

Document image analysis, imaging geometry, geometric correction, shape-from-X, mesh warping.

CITATION

Gaofeng Meng, Chunhong Pan, Shiming Xiang, Jiangyong Duan, "Metric Rectification of Curved Document Images",

*IEEE Transactions on Pattern Analysis & Machine Intelligence*, vol.34, no. 4, pp. 707-722, April 2012, doi:10.1109/TPAMI.2011.151REFERENCES