research-article

Higher order MRF for foreground-background separation in multi-spectral images of historical manuscripts

Authors:

Martin Lettner,

Robert SablatnigAuthors Info & Claims

DAS '10: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems

Pages 317 - 324

https://doi.org/10.1145/1815330.1815371

Published: 09 June 2010 Publication History

DAS '10: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems

Higher order MRF for foreground-background separation in multi-spectral images of historical manuscripts

Pages 317 - 324

Abstract
References

Abstract

Multi-spectral imaging for the analysis and preservation of ancient documents has gained high attention in recent years. While readability enhancement is based on the multi-spectral image corpus, foreground-background separation still relies mainly on gray level or color images. In this paper we propose a foreground-background separation algorithm designed for multi-spectral images. The main contribution is the simultaneously utilization of spectral and spatial features. While spectral features incorporate the spectral components of the multi-spectral images, the spatial features are based on stroke properties. Higher order Markov Random Fields enables an efficient way to combine both features. To solve higher order energy functions, we introduce a new message update rule in the well known belief propagation algorithm based on a higher order potential function.

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Cited By

Rahiche ACheriet M(2021)Blind Decomposition of Multispectral Document Images Using Orthogonal Nonnegative Matrix FactorizationIEEE Transactions on Image Processing10.1109/TIP.2021.308826630(5997-6012)Online publication date: 2021
https://doi.org/10.1109/TIP.2021.3088266
Salehani YArabnejad ERahiche ABakhta ACheriet M(2020)MSdB-NMF: MultiSpectral Document Image Binarization Framework via Non-Negative Matrix Factorization ApproachIEEE Transactions on Image Processing10.1109/TIP.2020.302361329(9099-9112)Online publication date: 2020
https://doi.org/10.1109/TIP.2020.3023613
Rahiche ABakhta ACheriet M(2019)Blind Source Separation Based Framework for Multispectral Document Images Binarization2019 International Conference on Document Analysis and Recognition (ICDAR)10.1109/ICDAR.2019.00237(1476-1481)Online publication date: Sep-2019
https://doi.org/10.1109/ICDAR.2019.00237
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cover image ACM Other conferences

DAS '10: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems

June 2010

490 pages

ISBN:9781605587738

DOI:10.1145/1815330

General Chairs:
David Doermann
University of Maryland, College Park
,
Venu Govindaraju
University at Buffalo, SUNY
,
Daniel Lopresti
Lehigh University
,
Prem Natarajan
Raytheon BBN Technologies

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 09 June 2010

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DAS '10

DAS '10: The Eighth IAPR International Workshop on Document Analysis Systems

June 9 - 11, 2010

Massachusetts, Boston, USA

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Cited By

Rahiche ACheriet M(2021)Blind Decomposition of Multispectral Document Images Using Orthogonal Nonnegative Matrix FactorizationIEEE Transactions on Image Processing10.1109/TIP.2021.308826630(5997-6012)Online publication date: 2021
https://doi.org/10.1109/TIP.2021.3088266
Salehani YArabnejad ERahiche ABakhta ACheriet M(2020)MSdB-NMF: MultiSpectral Document Image Binarization Framework via Non-Negative Matrix Factorization ApproachIEEE Transactions on Image Processing10.1109/TIP.2020.302361329(9099-9112)Online publication date: 2020
https://doi.org/10.1109/TIP.2020.3023613
Rahiche ABakhta ACheriet M(2019)Blind Source Separation Based Framework for Multispectral Document Images Binarization2019 International Conference on Document Analysis and Recognition (ICDAR)10.1109/ICDAR.2019.00237(1476-1481)Online publication date: Sep-2019
https://doi.org/10.1109/ICDAR.2019.00237
Hollaus FDiem MSablatnig R(2018)MultiSpectral Image Binarization using GMMs2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR)10.1109/ICFHR-2018.2018.00105(570-575)Online publication date: Aug-2018
https://doi.org/10.1109/ICFHR-2018.2018.00105
Hollaus FDiem MSablatnig R(2015)Binarization of MultiSpectral Document ImagesProceedings, Part II, of the 16th International Conference on Computer Analysis of Images and Patterns - Volume 925710.1007/978-3-319-23117-4_10(109-120)Online publication date: 2-Sep-2015
https://dl.acm.org/doi/10.1007/978-3-319-23117-4_10
Hedjam RCheriet M(2013)Ground-Truth Estimation in Multispectral Representation SpaceProceedings of the 2013 12th International Conference on Document Analysis and Recognition10.1109/ICDAR.2013.45(190-194)Online publication date: 25-Aug-2013
https://dl.acm.org/doi/10.1109/ICDAR.2013.45
Hedjam RCheriet MBarrett BBrown MManmatha RGehring J(2011)Combining statistical and geometrical classifiers for text extraction in multispectral document imagesProceedings of the 2011 Workshop on Historical Document Imaging and Processing10.1145/2037342.2037359(98-105)Online publication date: 16-Sep-2011
https://dl.acm.org/doi/10.1145/2037342.2037359
Hedjam RCheriet M(2011)Novel Data Representation for Text Extraction from Multispectral Historical Document ImagesProceedings of the 2011 International Conference on Document Analysis and Recognition10.1109/ICDAR.2011.43(172-176)Online publication date: 18-Sep-2011
https://dl.acm.org/doi/10.1109/ICDAR.2011.43
Kleber FDiem MSablatnig R(2011)Scale Space Binarization Using Edge Information Weighted by a Foreground EstimationProceedings of the 2011 International Conference on Document Analysis and Recognition10.1109/ICDAR.2011.238(1180-1184)Online publication date: 18-Sep-2011
https://dl.acm.org/doi/10.1109/ICDAR.2011.238

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