scikit-image: Image processing in Python

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1 Stellenbosch University, Stellenbosch, South Africa
2 Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
3 Victorian Life Sciences Computation Initiative, Carlton, VIC, Australia
4 Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ, USA
5 Department of Biomedical Engineering, Mayo Clinic, Rochester, MN, USA
6 AICBT Ltd, Oxford, UK
7 Joint Unit, CNRS / Saint Gobain, Aubervilliers, France
8 Enthought, Inc., Austin, TX, USA
DOI
10.7287/peerj.preprints.336v2
Published
Accepted
Subject Areas
Bioinformatics, Computational Biology, Computational Science, Human-Computer Interaction, Science and Medical Education
Keywords
image processing, reproducible research, education, visualization
Copyright
© 2014 van der Walt et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
Cite this article
van der Walt S, Schönberger JL, Nunez-Iglesias J, Boulogne F, Warner JD, Yager N, Gouillart E, Yu T, the scikit-image contributors. 2014. scikit-image: Image processing in Python. PeerJ PrePrints 2:e336v2

Abstract

scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal "Modified BSD" open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image.

Author Comment

We have added some missing references, changed others (webpages) to indicate authorship more clearly, and slightly improved the last figure.