Historical document image binarization: A review
This review provides a comprehensive view of the field of historical document image
binarization with a focus on the contributions made in the last decade. After the introduction …
binarization with a focus on the contributions made in the last decade. After the introduction …
DP-LinkNet: A convolutional network for historical document image binarization
W **ong, X Jia, D Yang, M Ai, L Li… - KSII Transactions on …, 2021 - koreascience.kr
Document image binarization is an important pre-processing step in document analysis and
archiving. The state-of-the-art models for document image binarization are variants of …
archiving. The state-of-the-art models for document image binarization are variants of …
An enhanced binarization framework for degraded historical document images
Binarization plays an important role in document analysis and recognition (DAR) systems. In
this paper, we present our winning algorithm in ICFHR 2018 competition on handwritten …
this paper, we present our winning algorithm in ICFHR 2018 competition on handwritten …
Degraded historical document image binarization using local features and support vector machine (SVM)
W **ong, J Xu, Z **ong, J Wang, M Liu - Optik, 2018 - Elsevier
This paper presents a support vector machine (SVM) based method for degraded historical
document image binarization. Given a degraded historical document image, the proposed …
document image binarization. Given a degraded historical document image, the proposed …
A non-parametric binarization method based on ensemble of clustering algorithms
Binarization of document images still attracts the researchers especially when degraded
document images are considered. This is evident from the recent Document Image …
document images are considered. This is evident from the recent Document Image …
A novel variational model for noise robust document image binarization
S Feng - Neurocomputing, 2019 - Elsevier
Binarization is a fundamental problem in document image analysis systems. Different from
current thresholding techniques, a novel variational model is proposed for noise robust …
current thresholding techniques, a novel variational model is proposed for noise robust …
Document binarization via multi-resolutional attention model with DRD loss
X Peng, C Wang, H Cao - 2019 International Conference on …, 2019 - ieeexplore.ieee.org
Document binarization which separates text from background is a critical pre-processing
step for many high level document analysis tasks. Conventional document binarization …
step for many high level document analysis tasks. Conventional document binarization …
A flexible dynamic partitioning algorithm for optimistic distributed simulation
P Peschlow, T Honecker… - … International Workshop on …, 2007 - ieeexplore.ieee.org
The performance of distributed simulation depends very much on the partitioning of the
simulation model among the participating hosts. Usually, when starting a simulation run, an …
simulation model among the participating hosts. Usually, when starting a simulation run, an …
An image thresholding approach based on Gaussian mixture model
L Zhao, S Zheng, W Yang, H Wei, X Huang - Pattern Analysis and …, 2019 - Springer
Image thresholding is an important technique for partitioning the image into foreground and
background in image processing and analysis. It is difficult for traditional thresholding …
background in image processing and analysis. It is difficult for traditional thresholding …
Coldbin: Cold diffusion for document image binarization
Document images, when captured in real-world settings, either modern or historical,
frequently exhibit various forms of degradation such as ink stains, smudges, faded text, and …
frequently exhibit various forms of degradation such as ink stains, smudges, faded text, and …