This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Restoring Warped Document Images through 3D Shape Modeling
February 2006 (vol. 28 no. 2)
pp. 195-208
Scanning a document page from a thick bound volume often results in two kinds of distortions in the scanned image, i.e., shade along the "spine” of the book and warping in the shade area. In this paper, we propose an efficient restoration method based on the discovery of the 3D shape of a book surface from the shading information in a scanned document image. From a technical point of view, this shape from shading (SFS) problem in real-world environments is characterized by 1) a proximal and moving light source, 2) Lambertian reflection, 3) nonuniform albedo distribution, and 4) document skew. Taking all these factors into account, we first build practical models (consisting of a 3D geometric model and a 3D optical model) for the practical scanning conditions to reconstruct the 3D shape of the book surface. We next restore the scanned document image using this shape based on deshading and dewarping models. Finally, we evaluate the restoration results by comparing our estimated surface shape with the real shape as well as the OCR performance on original and restored document images. The results show that the geometric and photometric distortions are mostly removed and the OCR results are improved markedly.

[1] H. Baird, “Document Image Defect Models,” Proc. Workshop Syntactic and Structural Pattern Recognition, pp. 38-46, June 1990.
[2] H. Baird, “Document Image Defect Models and Their Uses,” Proc. Int'l Conf. Document Analysis and Recognition, pp. 730-734, Oct. 1993.
[3] H. Baird, “Document Image Quality: Making Fine Discriminations,” Proc. Int'l Conf. Document Analysis and Recognition, pp. 459-462, Sept. 1999.
[4] Y.Y. Tang and C.Y. Suen, “Image Transformation Approach to Nonlinear Shape Restoration,” IEEE Trans. Systems, Man, and Cybernetics, vol. 23, no. 1, pp. 155-171, Jan./Feb. 1993.
[5] O. Lavaille, X. Molines, F. Angella, and P. Baylou, “Active Contours Network to Straighten Distorted Text Lines,” Proc. Int'l Conf. Image Processing, pp. 1074-1077, Oct. 2001.
[6] Y. Weng and Q. Zhu, “Nonlinear Shape Restoration for Document Images,” Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, pp. 568-573, 1996.
[7] Y.C. Tsoi and M.S. Brown, “Geometric and Shading Correction for Images of Printed Materials— A Unified Approach Using Boundary,” Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 240-246, 2004.
[8] Z. Zhang and C.L. Tan, “Restoration of Document Images Scanned from Thick Bound Document,” Proc. Int'l Conf. Image Processing, pp. 1074-1077, Oct. 2001.
[9] Z. Zhang and C.L. Tan, “Recovery of Distorted Document Image from Bound Volumes,” Proc. Int'l Conf. Document Analysis and Recognition, pp. 429-433, 2001.
[10] Z. Zhang and C.L. Tan, “Straightening Warped Text Lines Using Polynomial Regression,” Proc. Int'l Conf. Image Processing, pp. 977-980, Sept. 2002.
[11] Z. Zhang and C.L. Tan, “Correcting Document Image Warping Based on Regression of Curved Text Lines,” Proc. Int'l Conf. Document Analysis and Recognition, pp. 589-593, Aug. 2003.
[12] M. Pilu, “Undoing Page Curl Distortion Using Applicable Surfaces,” Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 67-72, Dec. 2001.
[13] M.S. Brown and W.B. Seales, “Image Restoration of Arbitrarily Warped Documents,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 10, pp. 1295-1306, 2004.
[14] A. Doncescu, A. Bouju, and V. Quillet, “Former Books Digital Processing: Image Warping,” Proc. Int'l Workshop Document Image Analysis, pp. 5-9, 1997.
[15] A. Yamashita, A. Kawarago, T. Kaneko, and K.T. Miura, “Shape Reconstruction and Image Restoration for Non-Flat Surface of Document with a Stereo Vision System,” Proc. Int'l Conf. Pattern Recognitiontion, 2004.
[16] H. Cao, X. Ding, and C. Liu, “A Cylindrical Model to Rectify the Bound Document Image,” Proc. Int'l Conf. Computer Vision, vol. 2, pp. 228-233, Oct. 2003.
[17] H. Cao, X. Ding, and C. Liu, “Rectifying the Bound Document Image Captured by the Camera: A Model Based Approach,” Proc. Int'l Conf. Computer Vision, vol. 1, pp. 71-74, Oct. 2003.
[18] T. Kanungo, R.M. Haralick, and I. Phillips, “Nonlinear Global and Local Document Degradation Models,” Int'l J. Imaging System and Technology, pp. 220-230, Oct. 1994.
[19] T. Wada, H. Ukida, and T. Matsuyama, “Shape from Shading with Interreflections under a Proximal Light Source: Distortion-Free Copying of an Unfolded Book,” Int'l J. Computer Vision, vol. 24, no. 2, pp. 125-135, 1997.
[20] Z. Zhang, C.L. Tan, and L.Y. Fan, “Estimation of 3D Shape of Warped Document Surface for Image Restoration,” Proc. Int'l Conf. Pattern Recognition, 2004.
[21] Z. Zhang, C.L. Tan, and L.Y. Fan, “Restoration of Curved Document Images through 3D Shape Modeling,” Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 10-16, 2004.
[22] M. Junker, R. Hoch, and A. Dengle, “On the Evaluation of Document Analysis Components by Recall, Precision and Accuracy,” Proc. Int'l Conf. Document Analysis and Recognition, pp. 713-716, 1999.
[23] H. Ragheb and E.R. Hancock, “Separating Lambertian and Specular Reflectance Components Using Iterated Conditional Modes,” Proc. British Machine Vision Conf., pp. 541-552, Sept. 2001.

Index Terms:
Index Terms- Document image restoration, document image analysis, shape from shading, image warping, image distortion, OCR improvement.
Citation:
Chew Lim Tan, Li Zhang, Zheng Zhang, Tao Xia, "Restoring Warped Document Images through 3D Shape Modeling," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, no. 2, pp. 195-208, Feb. 2006, doi:10.1109/TPAMI.2006.40
Usage of this product signifies your acceptance of the Terms of Use.