Illumination Compensation for Document Images Using Local-Global Block Analysis
IVIC '09 Proceedings of the 1st International Visual Informatics Conference on Visual Informatics: Bridging Research and Practice
Binarization of historical document images using the local maximum and minimum
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Markov random field based binarization for hand-held devices captured document images
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing
Efficient illumination compensation techniques for text images
Digital Signal Processing
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This paper presents a document image binarization tech- nique that segments text from badly illuminated document images. Based on the observations that text documents nor- mally lie over a planar or smoothly curved surface and have a uniformly colored background, badly illuminated docu- ment images are binarized by using a smoothing polynomial surface, which estimates the shading variation and com- pensates the shading degradation based on the estimated shading variation. Badly illuminated document images are accordingly binarized through the global thresholding of the compensated document images. Compared with the re- ported methods, the proposed technique is tolerant to the variations in text size and document contrast. At the same time, it is much faster and able to produce a binary text im- age with little background noise.