book · 2018

Document Image Processing

Ergina Kavallieratou, Laurence Likforman-Sulem

Cited by 3Open access

Abstract

The Special Issue "Document Image Processing" in the Journal of Imaging aims at presenting approaches which contribute to access the content of document images. These approaches are related to low level tasks such as image preprocessing, skew/slant corrections, binarization and document segmentation, as well as high level tasks such as OCR, handwriting recognition, word spotting or script identification. This special issue brings together 12 papers that discuss such approaches. The first three articles deal with historical document preprocessing. The work by Hanif et al. [1] aims at removing bleed-through using a non-linear model, and at reconstructing the background by an inpainting approach based on non-local patch similarity. The paper by Almeida et al. [2] proposes a new binarization approach that includes a decision-based process for finding the best threshold for each RGB channel. In the paper by Kavallieratou et al. [3], a segmentation-free approach based on the Wigner-Ville distribution is used to detect the slant of a document and correct it.

Cite this paper

APA 7

Kavallieratou, E., & Likforman-Sulem, L. (2018). Document Image Processing. https://doi.org/10.3390/books978-3-03897-106-1

MLA 9

Kavallieratou, Ergina, and Laurence Likforman-Sulem. “Document Image Processing.” 2018, https://doi.org/10.3390/books978-3-03897-106-1.

Chicago

Kavallieratou, Ergina, and Laurence Likforman-Sulem. 2018. “Document Image Processing.” https://doi.org/10.3390/books978-3-03897-106-1.

Harvard

Kavallieratou, E. and Likforman-Sulem, L. (2018) ‘Document Image Processing’. Available at: https://doi.org/10.3390/books978-3-03897-106-1.

BibTeX

@book{kavallieratou2018document,
  title = {{Document Image Processing}},
  author = {Kavallieratou, Ergina and Likforman-Sulem, Laurence},
  year = {2018},
  doi = {10.3390/books978-3-03897-106-1}
}

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