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|Title:||A framework for reducing ink-bleed in old documents|
|Citation:||Huang, Y.,Brown, M.S.,Xu, D. (2008). A framework for reducing ink-bleed in old documents. 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR. ScholarBank@NUS Repository. https://doi.org/10.1109/CVPR.2008.4587820|
|Abstract:||We describe a novel application framework to reduce the effects of ink-bleed in old documents. This task is treated as a classification problem where training-data is used to compute per-pixel likelihoods for use in a dual-layer Markov Random Field (MRF) that simultaneously labels image pixels of the front and back of a document as either foreground, background, or ink-bleed, while maintaining the integrity of foreground strokes. Our approach obtains better results than previous work without the need for assumptions about ink-bleed intensities or extensive parameter tuning. Our overall framework is detailed, including front and back image alignment, training-data collection, and the MRF formulation with associated likelihoods and intra- and inter-layer cost computations. ©2008 IEEE.|
|Source Title:||26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR|
|Appears in Collections:||Staff Publications|
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