Abstract
Document analysis and graphics recognition algorithms are normally applied to the processing of images of 2D documents scanned when flattened against a planar surface. Technological advancements in recent years have led to a situation in which digital cameras with high resolution are widely available. Consequently, traditional graphics recognition tasks may be updated to accommodate document images captured through a hand-held camera in an uncontrolled environment. In this paper the problem of perspective and geometric deformations correction in document images is discussed. The proposed approach uses the texture of a document image so as to infer the document structure distortion. A two-pass image warping algorithm is then used to correct the images. In addition to being language independent, the proposed approach may handle document images that include multiple fonts, math notations, and graphics. The de-warped images contain less distortions and so are better suited for existing text/graphics recognition techniques.
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References
G. Agam. Perspective and geometric correction for graphics recognition. In Proc. GREC’01, pages 395–407, Kingston, Ontario, 2001.
A. Amin, S. Fischer, A.F. Parkinson, and R. Shiu. Comparative study of skew algorithms. Journal of Electronic Imaging, 5(4):443–451, 1996.
H. Baird. Document image defect models. In Proc. SSPR’90, pages 38–46, 1990.
M.S. Brown and W.B. Seales. Document restoration using 3d shape: a general deskewing algorithm for arbitrarily warped documents. In Proc. ICCV’01, pages 367–374, Vancouver, BC, Jul. 2001. IEEE.
A. Doncescu, A. Bouju, and V. Quillet. Former books digital processing: image warping. In Proc. Workshop on Document Image Analysis, pages 5–9, San Juan, Puerto Rico, Jun. 1997.
David F. Rogers. Procedural elements for computer graphics. McGraw-Hill, second edition, 1998.
H. Fujisawa, H. Sako, Y. Okada, and S. Lee. Information capturing camera and developmental issues. In Proc. ICDAR’99, pages 205–208, 1999.
D.J. Ittner and H.S. Baird. Language-free layout analysis. In Proc. ICDAR’93, pages 336–340, Tsukuba, Japan, 1993.
T. Kanungo, R. Haralick, and I. Philips. Global and local document degradation models. In Proc. ICDAR’93, pages 730–734, 1993.
H. Li, D. Doermann, and O. Kia. Automatic text detection and tracking in digital video. IEEE Trans. Image Processing, 9(1):147–156, 2000.
J. Sauvola, T. Seppanen, S. Haapakoski, and M. Pietikainen. Adaptive document binarization. In Proc. ICDAR’97, pages 147–152, Ulm, Germany, Aug. 1997.
M. Sawaki, H. Murase, and N. Hagita. Character recognition in bookshelf images by automatic template selection. In Proc. ICPR’98, pages 1117–1120, Aug. 1998.
M. Shridhar, J.W.V. Miller, G. Houle, and L. Bijnagte. Recognition of license plate images: issues and perspectives. In Proc. ICDAR’99, pages 17–20, 1999.
G. Worlberg. Digital Image Warping. IEEE Computer Society Press, Los Alamitos, California, 1990.
Z. Zhang and C.L. Tan. Recovery of distorted document images from bound volumes. In Proc. ICDAR’01, pages 429–433, Seattle, WA, 2001.
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© 2002 Springer-Verlag Berlin Heidelberg
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Wu, C., Agam, G. (2002). Document Image De-warping for Text/Graphics Recognition. In: Caelli, T., Amin, A., Duin, R.P.W., de Ridder, D., Kamel, M. (eds) Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2002. Lecture Notes in Computer Science, vol 2396. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-70659-3_36
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DOI: https://doi.org/10.1007/3-540-70659-3_36
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