Please use this identifier to cite or link to this item: https://doi.org/10.1109/CVPR.2008.4587820
Title: A framework for reducing ink-bleed in old documents
Authors: Huang, Y.
Brown, M.S. 
Xu, D.
Issue Date: 2008
Source: 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
URI: http://scholarbank.nus.edu.sg/handle/10635/40681
ISBN: 9781424422432
DOI: 10.1109/CVPR.2008.4587820
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