Textline information extraction from grayscale camera-captured document images
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
A new algorithm for segmenting warped text-lines in document images
Proceedings of the 2011 ACM Symposium on Applied Computing
An experimental workflow development platform for historical document digitisation and analysis
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing
Correcting book binding distortion in scanned documents
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
A new method for text-line segmentation for warped documents
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
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Dewarping of camera document images has attracted a lot of interest over the last few years since warping not only reduces the document readability but also affects the accuracy of an OCR application. In this paper, a two-step approach for efficient dewarping of camera document images is presented. At a first step, a coarse dewarping is accomplished with the help of a transformation model which maps the projection of a curved surface to a 2D rectangular area. The projection of the curved surface is delimited by the two curved lines which fit the top and bottom text lines along with the two straight lines which fit to the left and right text boundaries. At a second step, fine dewarping is achieved based on words detection. All words are pose normalized guided by the lower and upper word baselines. Experimental results on several camera document images demonstrate the robustness and effectiveness of the proposed technique.