[ANN] ImageBinarization.jl - Automatically binarize images into background and foreground

The ImageBinarization package provides numerous algorithms for transforming an image into a bi-level image (black background and white foreground). The initial release implements the following algorithms:

  1. Bradley, D. (2007). Adaptive Thresholding using Integral Image. Journal of Graphic Tools, 12(2), pp.13-21. doi:10.1080/2151237x.2007.10129236

  2. “BI-LEVEL IMAGE THRESHOLDING - A Fast Method”, Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing, 2008. Available: 10.5220/0001064300700076

  3. J. N. Kapur, P. K. Sahoo, and A. K. C. Wong, “A new method for gray-level picture thresholding using the entropy of the histogram,” Computer Vision, Graphics, and Image Processing, vol. 29, no. 1, p. 140, Jan. 1985.doi:10.1016/s0734-189x(85)90156-2

  4. C. A. Glasbey, “An Analysis of Histogram-Based Thresholding Algorithms,” CVGIP: Graphical Models and Image Processing, vol. 55, no. 6, pp. 532–537, Nov. 1993. doi:10.1006/cgip.1993.1040

  5. J. Kittler and J. Illingworth, “Minimum error thresholding,” Pattern Recognition, vol. 19, no. 1, pp. 41–47, Jan. 1986. doi:10.1016/0031-3203(86)90030-0

  6. J. M. S. Prewitt and M. L. Mendelsohn, “THE ANALYSIS OF CELL IMAGES,” Annals of the New York Academy of Sciences, vol. 128, no. 3, pp. 1035–1053, Dec. 2006.

  7. W.-H. Tsai, “Moment-preserving thresolding: A new approach,” Computer Vision, Graphics, and Image Processing, vol. 29, no. 3, pp. 377–393, Mar. 1985. doi:10.1016/0734-189x(85)90133-1

  8. J. Sauvola and M. Pietikäinen (2000). “Adaptive document image binarization”. Pattern Recognition 33 (2): 225-236. doi:10.1016/S0031-3203(99)00055-2

  9. Nobuyuki Otsu (1979). “A threshold selection method from gray-level histograms”. IEEE Trans. Sys., Man., Cyber. 9 (1): 62–66. doi:10.1109/TSMC.1979.4310076

  10. R. E. Vidal, “Generalized Principal Component Analysis (GPCA): An Algebraic Geometric Approach to Subspace Clustering and Motion Segmentation.” Order No. 3121739, University of California, Berkeley, Ann Arbor, 2003.

  11. Faisal Shafait, Daniel Keysers and Thomas M. Breuel (2008). “Efficient implementation of local adaptive thresholding techniques using integral images”. Proc. SPIE 6815, Document Recognition and Retrieval XV, 681510 (28 January 2008). doi:10.1117/12.767755

  12. P. L. Rosin, “Unimodal thresholding,” Pattern Recognition, vol. 34, no. 11, pp. 2083–2096, Nov. 2001.doi:10.1016/s0031-3203(00)00136-9

  13. Yen JC, Chang FJ, Chang S (1995), “A New Criterion for Automatic Multilevel Thresholding”, IEEE Trans. on Image Processing 4 (3): 370-378, doi:10.1109/83.366472

Some algorithms are particularly well-suited for binarizing text documents. Many of the algorithms are actually implemented in the companion package HistogramThresholding which currently operates at the level of one-dimensional histograms and not images.

The package was conceptualized and developed during the University of Adelaide Summer School Scholarship 2019 program and includes valuable contributions from:

  1. Abbey McCarthy
  2. Isabella Scalzi
  3. Tristan Betterman
  4. Wen Siang Tan
  5. Robert Woods
  6. William Godfrey

You will find important details about the various algorithms in the package documentation.

We hope you will find the algorithms useful in your own work.

Best wishes,

Zygmunt Szpak


Really nice, keep up the nice work !