Journal ArticleDOI
Adaptive degraded document image binarization
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TLDR
The proposed method does not require any parameter tuning by the user and can deal with degradations which occur due to shadows, non-uniform illumination, low contrast, large signal-dependent noise, smear and strain.About:
This article is published in Pattern Recognition.The article was published on 2006-03-01. It has received 585 citations till now. The article focuses on the topics: Thresholding & Wiener filter.read more
Citations
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Journal ArticleDOI
A combined approach for the binarization of handwritten document images
TL;DR: A combination of a global and a local adaptive binarization method at connected component level is proposed that aims in an improved overall performance and achieves top performance after extensive testing on the DIBCO (Document Image Binarization Contest) series datasets.
Journal ArticleDOI
Segmentation of historical machine-printed documents using Adaptive Run Length Smoothing and skeleton segmentation paths
TL;DR: Use of a novel Adaptive Run Length Smoothing Algorithm (ARLSA) in order to face the problem of complex and dense document layout, and detection of noisy areas and punctuation marks that are usual in historical machine-printed documents.
Journal ArticleDOI
DeepOtsu: Document enhancement and binarization using iterative deep learning
Sheng He,Lambertus Schomaker +1 more
TL;DR: The proposed method provides a new, clean version of the degraded image, one that is suitable for visualization and which shows promising results for binarization using Otsu’s global threshold, based on enhanced images learned iteratively by the neural network.
Journal ArticleDOI
A double-threshold image binarization method based on edge detector
TL;DR: This paper presents a new double-threshold image binarization method based on the edge and intensity information that is effective on thebinarization of images with low contrast, noise and non-uniform illumination.
A Double-Threshold Image Binarization Method based on Edge Detector Pattern Recognition
TL;DR: Zhang et al. as mentioned in this paper proposed a double-threshold image binarization method based on the edge and intensity information, which first finds seeds near the image edges and then uses closed image edges to partition the binarized image that is generated using a high threshold.
References
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Journal Article
Binary codes capable of correcting deletions, insertions, and reversals
Book
Fundamentals of digital image processing
TL;DR: This chapter discusses two Dimensional Systems and Mathematical Preliminaries and their applications in Image Analysis and Computer Vision, as well as image reconstruction from Projections and image enhancement.
Journal ArticleDOI
Survey over image thresholding techniques and quantitative performance evaluation
Mehmet Sezgin,Bulent Sankur +1 more
TL;DR: 40 selected thresholding methods from various categories are compared in the context of nondestructive testing applications as well as for document images, and the thresholding algorithms that perform uniformly better over nonde- structive testing and document image applications are identified.