Fast Restoration of Warped Document Image based on Text Rectangle Area Segmentation

The warp problems usually make the documents being hardly recognized. Specifically, when we copy a page of a thick book or bound document by digital photocopier, the resulted image is usually warped because of the thickness of the document. We focus on this problem and propose a fast method to restore the warped document image in this paper. The text rectangle area of the document is one of the features of a document. The morphological operation is utilized for text rectangle area segmentation. The DLT method is used to compute the mapping relations between the warped document and the non-warped document. In experimental results, the proposed method works on high resolution image very quickly. The warping text and the figures in documents have been restored by the proposed method successfully. This method is efficiency and fast for implementing on the module of digital photocopier.

[1]  Yu Zhang,et al.  A fast and stable approach for restoration of warped document images , 2005, Eighth International Conference on Document Analysis and Recognition (ICDAR'05).

[2]  Linda G. Shapiro,et al.  Computer Vision , 2001 .

[3]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[4]  W. Brent Seales,et al.  Image restoration of arbitrarily warped documents , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Ioannis Pratikakis,et al.  Segmentation Based Recovery of Arbitrarily Warped Document Images , 2007 .

[6]  Yu Zhang,et al.  Arbitrary warped document image restoration based on segmentation and Thin-Plate Splines , 2008, 2008 19th International Conference on Pattern Recognition.

[7]  Christoph H. Lampert,et al.  Document image dewarping using robust estimation of curled text lines , 2005, Eighth International Conference on Document Analysis and Recognition (ICDAR'05).

[8]  Bin Fu,et al.  A Model Based Book Dewarping Method to Handle 2D Images Captured by a Digital Camera , 2007, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007).

[9]  Jianhua Liu,et al.  Research on Contour Correction in Medical CT Image Segmentation , 2012, J. Comput..

[10]  Wangbo Zhang,et al.  Perspective Correction Method for Chinese Document Images , 2008, 2008 International Symposium on Intelligent Information Technology Application Workshops.

[11]  Xiaofeng Li,et al.  Gaussian Kernelized Fuzzy c-means with Spatial Information Algorithm for Image Segmentation , 2012, J. Comput..

[12]  Zhao Zhang,et al.  Estimation of 3D shape of warped document surface for image restoration , 2004, ICPR 2004.

[13]  Azriel Rosenfeld,et al.  Computer Vision , 1988, Adv. Comput..

[14]  Wayne Niblack,et al.  An introduction to digital image processing , 1986 .

[15]  Chew Lim Tan,et al.  Warped Document Image Restoration Using Shape-from-Shading and Physically-Based Modeling , 2007, 2007 IEEE Workshop on Applications of Computer Vision (WACV '07).

[16]  Nixon,et al.  Feature Extraction & Image Processing , 2008 .

[17]  Chew Lim Tan,et al.  RestoringWarped Document Images using Shape-from-Shading and Surface Interpolation , 2006, 18th International Conference on Pattern Recognition (ICPR'06).