Extrapolation, Interpolation, and Smoothing of Stationary Time Series
Extrapolation, Interpolation, and Smoothing of Stationary Time Series
Motion Deblurring for Optical Character Recognition
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Removing camera shake from a single photograph
ACM SIGGRAPH 2006 Papers
Image deblurring with blurred/noisy image pairs
ACM SIGGRAPH 2007 papers
High-quality motion deblurring from a single image
ACM SIGGRAPH 2008 papers
Binarization of historical document images using the local maximum and minimum
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Two-phase kernel estimation for robust motion deblurring
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
An effective document image deblurring algorithm
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
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Motion blur often decreases the quality of document image and makes the text information within the document images unreachable by optical character recognition (OCR) or by a person. This paper presents a blur correction technique that aims to correct motion blur within document images. Given a blurred document image, an alpha channel map is first constructed based on specific image characteristics that are associated with text documents. Several blur parameters including blur direction and blur extent are then estimated from the constructed alpha channel map. Finally the blurred document image is restored by using Richardson-Lucy deconvolution technique based on the estimated blur parameters. Experiments on a number of document images with motion blur show that the proposed technique improves the document visual quality as well as the OCR performance significantly.