skip to main content
10.1145/1816123.1816161acmconferencesArticle/Chapter ViewAbstractPublication PagesjcdlConference Proceedingsconference-collections
short-paper

BinarizationShop: a user-assisted software suite for converting old documents to black-and-white

Published: 21 June 2010 Publication History

Abstract

Converting a scanned document to a binary format (black and white) is a key step in the digitization process. While many existing binarization algorithms operate robustly for well-kept documents, these algorithms often produce less than satisfactory results when applied to old documents, especially those degraded with stains and other discolorations. For these challenging documents, user assistance can be advantageous in directing the binarization procedure. Many existing algorithms, however, are poorly designed to incorporate user assistance. In this paper, we discuss a software framework, BinarizationShop, that combines a series of binarization approaches that have been tailored to exploit user assistance. This framework provides a practical approach for converting difficult documents to black and white.

References

[1]
A. Dekhtyar, I. E. Iacob, J. Jaromczyk, K. Kiernan, N. Moore, and C. Porter. Building image-based electronic editions using the edition production technology. In ACM/IEEE Joint Conference on Digital Libraries (JCDL), 2005.
[2]
R. O. Duda, P. E. Hart, and D. G. Stork. Pattern Classification. Wiley-Interscience Publication, 2000.
[3]
B. Gatos, I. Pratikakis, and S. J. Perantonis. Adaptive degraded document image binarization. Pattern Recognition, 39:317--327, 2006.
[4]
Y. Huang and M. S. Brown. User-assisted ink--bleed correction for handwritten documents. In ACM/IEEE Joint Conference on Digital Libraries (JCDL), 2008.
[5]
J. N. Kapur, P. K. Sahoo, and A. K. C. Wong. A new method for graylevel picture thresholding using the entropy of the histogram. Computer Vision, Graphics, and Image Processing, 29:273--285, 1985.
[6]
C. G. Leedham, C. Yan, K. Takru, J. H. N. Tan, and L. Mian. Comparison of some thresholding algorithms for text/background segmentation in difficult document images. In International Conference on Document Analysis and Recognition (ICDAR), 2003.
[7]
Z. Lu, Z. Wu, and M. S. Brown. Interactive degraded document binarization: An example (and case) for interactive computer vision. In IEEE Workshop on Application of Computer Vision (WACV), 2009.
[8]
C. Monroy, R. Furuta, and G. Stringer. Digital donne: workflow, editing tools, and the reader's interface of a collection of 17th-century english poetry. In ACM/IEEE Joint Conference on Digital Libraries (JCDL), 2007.
[9]
W. Niblack. An Introduction to Digital Image Processing. Prentice-Hall, Englewood Cliffs, NJ, 1986.
[10]
N. Otsu. A threshold selection method from gray level histograms. IEEE Transactions on Systems, Man and Cybernetics, 9:62--66, 1979.
[11]
J. Sauvola and M. Pietikainen. Adaptive document image binarization. Pattern Recognition, 33:225--236, 2000.
[12]
W. B. Seales and Y. Lin. Digital restoration using volumetric scanning. In ACM/IEEE Joint Conference on Digital Libraries (JCDL), 2004.
[13]
B. Wingenroth, M. Patton, and T. DiLauro. Enhancing access to the levy sheet music collection. In ACM/IEEE Joint Conference on Digital Libraries (JCDL), 2002.

Cited By

View all
  • (2024)DocRes: A Generalist Model Toward Unifying Document Image Restoration Tasks2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.01482(15654-15664)Online publication date: 16-Jun-2024
  • (2024)Three-stage binarization of color document images based on discrete wavelet transform and generative adversarial networksKnowledge-Based Systems10.1016/j.knosys.2024.112542304(112542)Online publication date: Nov-2024
  • (2024)A Dilated MultiRes Visual Attention U-Net for historical document image binarizationSignal Processing: Image Communication10.1016/j.image.2024.117102122(117102)Online publication date: Mar-2024
  • Show More Cited By

Index Terms

  1. BinarizationShop: a user-assisted software suite for converting old documents to black-and-white

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image ACM Conferences
      JCDL '10: Proceedings of the 10th annual joint conference on Digital libraries
      June 2010
      424 pages
      ISBN:9781450300858
      DOI:10.1145/1816123
      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]

      Sponsors

      In-Cooperation

      • IEEE CS

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 21 June 2010

      Permissions

      Request permissions for this article.

      Check for updates

      Author Tags

      1. binarization
      2. document processing
      3. user-assisted software

      Qualifiers

      • Short-paper

      Conference

      JCDL10
      Sponsor:
      JCDL10: Joint Conference on Digital Libraries
      June 21 - 25, 2010
      Queensland, Gold Coast, Australia

      Acceptance Rates

      Overall Acceptance Rate 415 of 1,482 submissions, 28%

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)5
      • Downloads (Last 6 weeks)1
      Reflects downloads up to 02 Mar 2025

      Other Metrics

      Citations

      Cited By

      View all
      • (2024)DocRes: A Generalist Model Toward Unifying Document Image Restoration Tasks2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.01482(15654-15664)Online publication date: 16-Jun-2024
      • (2024)Three-stage binarization of color document images based on discrete wavelet transform and generative adversarial networksKnowledge-Based Systems10.1016/j.knosys.2024.112542304(112542)Online publication date: Nov-2024
      • (2024)A Dilated MultiRes Visual Attention U-Net for historical document image binarizationSignal Processing: Image Communication10.1016/j.image.2024.117102122(117102)Online publication date: Mar-2024
      • (2024)Binarizing Documents by Leveraging both Space and FrequencyDocument Analysis and Recognition - ICDAR 202410.1007/978-3-031-70543-4_1(3-22)Online publication date: 9-Sep-2024
      • (2023)Historical Text Image Enhancement Using Image Scaling and Generative Adversarial NetworksSensors10.3390/s2308400323:8(4003)Online publication date: 14-Apr-2023
      • (2023)Diffusion-Denoising Process with Gated U-Net for High-Quality Document BinarizationApplied Sciences10.3390/app13201114113:20(11141)Online publication date: 10-Oct-2023
      • (2023)A Review of Document Image Enhancement Based on Document Degradation ProblemApplied Sciences10.3390/app1313785513:13(7855)Online publication date: 4-Jul-2023
      • (2023)A Novel Degraded Document Binarization Model through Vision Transformer NetworkInformation Fusion10.1016/j.inffus.2022.12.01193(159-173)Online publication date: May-2023
      • (2023)CCDWT-GAN: Generative Adversarial Networks Based on Color Channel Using Discrete Wavelet Transform for Document Image BinarizationPRICAI 2023: Trends in Artificial Intelligence10.1007/978-981-99-7019-3_19(186-198)Online publication date: 10-Nov-2023
      • (2023)Context Aware Document Binarization and Its Application to Information Extraction from Structured DocumentsDocument Analysis and Recognition - ICDAR 202310.1007/978-3-031-41676-7_4(63-78)Online publication date: 19-Aug-2023
      • Show More Cited By

      View Options

      Login options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Figures

      Tables

      Media

      Share

      Share

      Share this Publication link

      Share on social media