https://github.com/manuelaguadomtz/pythreshold
PyThreshold is a python package featuring Numpy/Scipy implementations of state-of-the-art image thresholding algorithms.
https://github.com/manuelaguadomtz/pythreshold
image-processing image-th
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PyThreshold is a python package featuring Numpy/Scipy implementations of state-of-the-art image thresholding algorithms.
- Host: GitHub
- URL: https://github.com/manuelaguadomtz/pythreshold
- Owner: manuelaguadomtz
- License: mit
- Created: 2018-08-28T13:58:18.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2022-08-28T12:40:34.000Z (almost 4 years ago)
- Last Synced: 2025-09-22T21:33:35.853Z (9 months ago)
- Topics: image-processing, image-th
- Language: Python
- Homepage:
- Size: 86.9 KB
- Stars: 57
- Watchers: 4
- Forks: 19
- Open Issues: 9
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
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README
# PyThreshold
**PyThreshold** is a python package featuring Numpy/Scipy implementations of state-of-the-art image thresholding algorithms.
## Installing
**PyThreshold** can be easily installed by typing the following command
pip install pythreshold
## Usage
from pythreshold.utils import test_thresholds
from scipy.misc import ascent
# Testing all the included thresholding algorithms
test_thresholds()
# Testing all the included thresholding algorithms using a custom image
img = ascent()
test_thresholds(img)
Or just type in a terminal:
pythreshold -i /path/to/input/image -o /output/directory/for/thresholded/images
## Included Algorithms
* Global thresholding
* Parker, J. R. (2010). Algorithms for image processing and
computer vision. John Wiley & Sons. (**Two peaks**)
* Parker, J. R. (2010). Algorithms for image processing and
computer vision. John Wiley & Sons. (**p-tile**)
* Otsu, Nobuyuki. "A threshold selection method from gray-level
histograms." IEEE transactions on systems, man, and cybernetics
9.1 (1979): 62-66.
* Kittler, J. and J. Illingworth. "On Threshold Selection Using Clustering
Criteria,"" IEEE Transactions on Systems, Man, and Cybernetics 15, no. 5
(1985): 652–655.
* Entropy thresholding
* Johannsen, G., and J. Bille "A Threshold Selection Method Using
Information Measures,"" Proceedings of the Sixth International Conference
on Pattern Recognition, Munich, Germany (1982): 140–143.
* Kapur, J. N., 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 29, no. 3 (1985): 273–285.
* Pun, T. "A New Method for Grey-Level Picture Thresholding Using the
Entropy of the Histogram,"" Signal Processing 2, no. 3 (1980): 223–237.
* Global thresholding (Multi-threshold)
* Liao, Ping-Sung, Tse-Sheng Chen, and Pau-Choo Chung. "A fast algorithm
for multilevel thresholding." J. Inf. Sci. Eng. 17.5 (2001): 713-727.
* Entropy thresholding
* Kapur, J. N., 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 29, no. 3 (1985): 273–285.
* Local thresholding
* Bernsen, J (1986), "Dynamic Thresholding of Grey-Level Images",
Proc. of the 8th Int. Conf. on Pattern Recognition
* Bradley, D., & Roth, G. (2007). Adaptive thresholding
using the integral image. Journal of Graphics Tools, 12(2), 13-21.
* Parker, J. R. (2010). Algorithms for image processing and
computer vision. John Wiley & Sons. (**Contrast thresholding**)
* Meng-Ling Feng and Yap-Peng Tan, "Contrast adaptive thresholding of
low quality document images", IEICE Electron. Express, Vol. 1, No.
16, pp.501-506, (2004).
* Parker, J. R. (2010). Algorithms for image processing and
computer vision. John Wiley & Sons. (**Local mean thresholding**)
* Niblack, W.: "An introduction to digital image
processing" (Prentice- Hall, Englewood Cliffs, NJ, 1986), pp. 115–116
* Sauvola, J., Seppanen, T., Haapakoski, S., and Pietikainen, M.:
"Adaptive document thresholding". Proc. 4th Int. Conf. on Document
Analysis and Recognition, Ulm Germany, 1997, pp. 147–152.
* Singh, O. I., Sinam, T., James, O., & Singh, T. R. (2012). Local contrast
and mean based thresholding technique in image binarization. International
Journal of Computer Applications, 51, 5-10.
* C. Wolf, J-M. Jolion, "Extraction and Recognition of Artificial Text in
Multimedia Documents", Pattern Analysis and Applications, 6(4):309-326, (2003).
## Additional Information
Do you find **PyThreshold** useful? You can collaborate with us:
[GitHub](https://github.com/manuelaguadomtz/pythreshold)
Additional materials and information can be found at:
[ResearchGate](https://www.researchgate.net/project/Numpy-Scipy-implementations-of-image-thresholding-algorithms>)