scikit-image

scikit-image (formerly scikits.image) is an open-source image processing library for the Python programming language.[2] It includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more.[3] It is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

scikit-image
Original author(s)Stéfan van der Walt
Initial releaseAugust 2009 (2009-08)
Stable release
0.22.0[1] / 3 October 2023 (3 October 2023)
Repository
Written inPython, Cython, and C.
Operating systemLinux, Mac OS X, Microsoft Windows
TypeLibrary for image processing
LicenseBSD License
Websitescikit-image.org

Overview

The scikit-image project started as scikits.image, by Stéfan van der Walt. Its name stems from the notion that it is a "SciKit" (SciPy Toolkit), a separately-developed and distributed third-party extension to SciPy.[4] The original codebase was later extensively rewritten by other developers. Of the various scikits, scikit-image as well as scikit-learn were described as "well-maintained and popular" in November 2012.[5] Scikit-image has also been active in the Google Summer of Code.[6]

Implementation

scikit-image is largely written in Python, with some core algorithms written in Cython to achieve performance.

References
  1. "Release 0.22.0". 3 October 2023. Retrieved 20 October 2023.
  2. S van der Walt; JL Schönberger; J Nunez-Iglesias; F Boulogne; JD Warner; N Yager; E Gouillart; T Yu; the scikit-image contributors (2014). "scikit-image: image processing in Python". PeerJ. 2:e453: e453. arXiv:1407.6245. Bibcode:2014PeerJ...2..453V. doi:10.7717/peerj.453. PMC 4081273. PMID 25024921. {{cite journal}}: |author9= has generic name (help)
  3. Chiang, Eric (2014). "Image Processing with scikit-image".
  4. Dreijer, Janto. "scikit-image".
  5. Eli Bressert (2012). SciPy and NumPy: an overview for developers. O'Reilly. p. 43. ISBN 9781449361624.
  6. Birodkar, Vighnesh (2014). "GSOC 2014 – Signing Off".
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