Document Image De-warping for Text/Graphics Recognition
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Correcting Document Image Warping Based on Regression of Curved Text Lines
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Restoring Warped Document Images through 3D Shape Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape from shading for the digitization of curved documents
Machine Vision and Applications
Restoration of arbitrarily warped document images based on text line and word detection
SPPR'07 Proceedings of the Fourth conference on IASTED International Conference: Signal Processing, Pattern Recognition, and Applications
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Restoration of arbitrarily warped document images based on text line and word detection
SPPRA '07 Proceedings of the Fourth IASTED International Conference on Signal Processing, Pattern Recognition, and Applications
Shape from contour for the digitization of curved documents
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
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Abstract: Recovery of document images scanned from thick bound volumes is necessary for the purpose of human reading and text retrieval. The main problem with scanning of bound volumes is that there always occurs perspective distortion. Such distortion causes two sources of degradation for the scanned images - 1) shadow at the book spine area, and 2) warping of the words in the shadow. In this paper, we have developed a restoration system to solve these two problems. First, the boundary between the shadow and the clean area is detected. Then the system applies a modified Niblack's method to remove the shadow. The system uses a connected component analysis to help improve the noise reduction and adjust the location and orientation of the warped word in the shadow area, i.e. the words within the boundary detected earlier. The implementation results for each step are presented. Our system will be used in the text retrieval projects for National Archives of Singapore and NUS Digital Library.