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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.
Index Terms- Document image restoration, document image analysis, shape from shading, image warping, image distortion, OCR improvement.

C. L. Tan, Z. Zhang, L. Zhang and T. Xia, "Restoring Warped Document Images through 3D Shape Modeling," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 28, no. , pp. 195-208, 2006.
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