https://github.com/mlampros/superpixelimagesegmentation

Image Segmentation using Superpixels, Affinity Propagation and Kmeans Clustering
https://github.com/mlampros/superpixelimagesegmentation

affinity-propagation kmeans mini-batch-kmeans slic superpixels

Last synced: 25 days ago
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Image Segmentation using Superpixels, Affinity Propagation and Kmeans Clustering

• Host: GitHub
• URL: https://github.com/mlampros/superpixelimagesegmentation
• Owner: mlampros
• Created: 2018-11-08T20:02:09.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2023-05-27T04:33:41.000Z (almost 2 years ago)
• Last Synced: 2025-03-26T02:42:57.927Z (about 1 month ago)
• Topics: affinity-propagation, kmeans, mini-batch-kmeans, slic, superpixels
• Language: R
• Homepage: https://mlampros.github.io/SuperpixelImageSegmentation/
• Size: 339 KB
• Stars: 19
• Watchers: 4
• Forks: 6
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        

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## SuperpixelImageSegmentation




The R / Rcpp code of the *SuperpixelImageSegmentation* package is based primarily on the article ["Image Segmentation using SLIC Superpixels and Affinity Propagation Clustering", Bao Zhou, International Journal of Science and Research (IJSR), 2013](https://www.ijsr.net/archive/v4i4/SUB152869.pdf).

I wrote a [blog post](http://mlampros.github.io/2018/11/09/Image_Segmentation_Superpixels_Clustering/) explaining how to take advantage of the R / Rcpp code of the *SuperpixelImageSegmentation* package.




System / Software Requirements:

* [OpenImageR ](https://github.com/mlampros/OpenImageR)

* [ClusterR ](https://github.com/mlampros/ClusterR)

* a C++ 11 compiler





The *SuperpixelImageSegmentation* package can be installed from CRAN using,




```R

install.packages("SuperpixelImageSegmentation")

 

```




**or** by using the *install_github* function of the devtools package,





```R

remotes::install_github('mlampros/SuperpixelImageSegmentation')

```




**or** by directly downloading the .zip file using the **Clone or download** button in the [repository page](https://github.com/mlampros/SuperpixelImageSegmentation), extracting it locally (renaming it to *SuperpixelImageSegmentation* if necessary) and running,




```R

#--------

# on Unix

#--------

setwd('/your_folder/SuperpixelImageSegmentation/')

Rcpp::compileAttributes(verbose = TRUE)

setwd('/your_folder/')

system("R CMD build SuperpixelImageSegmentation")

system("R CMD INSTALL SuperpixelImageSegmentation_1.0.0.tar.gz")

#-----------

# on Windows

#-----------

setwd('C:/your_folder/SuperpixelImageSegmentation/')

Rcpp::compileAttributes(verbose = TRUE)

setwd('C:/your_folder/')

system("R CMD build SuperpixelImageSegmentation")

system("R CMD INSTALL SuperpixelImageSegmentation_1.0.0.tar.gz")

```




Use the following link to report bugs/issues,





[https://github.com/mlampros/SuperpixelImageSegmentation/issues](https://github.com/mlampros/SuperpixelImageSegmentation/issues)




### **Citation:**

If you use the code of this repository in your paper or research please cite both **SuperpixelImageSegmentation** and the **original articles / software** `https://CRAN.R-project.org/package=SuperpixelImageSegmentation`:




```R

@Manual{,

  title = {{SuperpixelImageSegmentation}: Image Segmentation using

    Superpixels, Affinity Propagation and Kmeans Clustering},

  author = {Lampros Mouselimis},

  year = {2022},

  note = {R package version 1.0.5},

  url =

    {https://CRAN.R-project.org/package=SuperpixelImageSegmentation},

}

```