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scikit-image: image processing in Python

Authors: van der Walt, Stefan; Schönberger, Johannes L.; Nunez-Iglesias, Juan; Boulogne, François; Warner, Joshua D.; Yager, Neil; Gouillart, Emmanuelle; +2 Authors

scikit-image: image processing in Python

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.

Countries
France, South Africa, France, Australia
Keywords

FOS: Computer and information sciences, QH301-705.5, Bioinformatics, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, scikit-image, Reproducible research, Python (Computer program language), Education, Image processing, Biology (General), Visualization, 000, R, Open source software, Open source, [PHYS.COND.CM-MS] Physics [physics]/Condensed Matter [cond-mat]/Materials Science [cond-mat.mtrl-sci], 004, Image processing -- Digital techniques -- Software, Medicine, Computer Science - Mathematical Software, Mathematical Software (cs.MS), Python

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5K
Top 0.01%
Top 0.01%
Top 0.1%
Green
gold