https://github.com/ahmdtaha/textureclassification_filterbank

This repos provides an MATLAB code implementation for the Statistical Approach to Texture Classification from Single Images paper by Varma et. al.
https://github.com/ahmdtaha/textureclassification_filterbank

classification-toolbox columbia-utrecht-dataset matlab texture-classification varma

Last synced: 7 months ago
JSON representation

This repos provides an MATLAB code implementation for the Statistical Approach to Texture Classification from Single Images paper by Varma et. al.

• Host: GitHub
• URL: https://github.com/ahmdtaha/textureclassification_filterbank
• Owner: ahmdtaha
• License: bsd-2-clause
• Created: 2016-02-08T12:46:22.000Z (about 10 years ago)
• Default Branch: master
• Last Pushed: 2018-01-30T18:57:13.000Z (about 8 years ago)
• Last Synced: 2025-04-10T16:53:07.873Z (12 months ago)
• Topics: classification-toolbox, columbia-utrecht-dataset, matlab, texture-classification, varma
• Language: Matlab
• Homepage:
• Size: 16.6 KB
• Stars: 12
• Watchers: 1
• Forks: 6
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          

Statistical Approach to Texture Classification from Single Images

-----------------------------------------------------------------

This repos provides an implementation for the "[Statistical Approach to Texture Classification from Single Images](http://www.robots.ox.ac.uk/~vgg/publications/2005/Varma05/)" paper by Varma et. al.

The filters (RFS, LM, S) used in this repos are from [this link](http://www.robots.ox.ac.uk/~vgg/research/texclass/filters.html)

It is not documented yet. Since I know that it will take me some time to write the documentation, I decided to provide this initial version of the code. There is a lot of work that can help make this code better. So any contributions will be welcomed.

Libraries

---------

To be able to run this code, you need to download the following libraries

 - [VLFeat open source library](http://www.vlfeat.org/)

 - [Classification toolbox for MATLAB, by Milano Chemometrics and QSAR Research Group](http://michem.disat.unimib.it/chm/download/softwares/help_classification/web.htm). 

 

 VLFeat Library is used to calculate K-means (vl_kmeans) and the distance between new  nodes and pre-computed centroids (vl_alldist).

 Classification toolbox is used to find the nearest neighbor during the classification phase.

Setup

-----

 1. Download the code.

 2. Download the [Classification toolbox for 

 3. MATLAB, by Milano Chemometrics and QSAR Research Group](http://michem.disat.unimib.it/chm/download/softwares/help_classification/web.htm). 

 3. Update the knn_calc_dist.m file with the file inside this repos, to support chi-square distance

 4. Update the "rootpath" variable in demo_curet.m to point to Columbia-Utrecht dataset folder on your machine.

 5. Run demo_curet.m to test the performance over Columbia-Utrecht dataset.

I will try to update the documentation incrementally to provide more instructions to make using this code easier.

Contributor list

----------------

1. [Ahmed Taha](http://ahmed-taha.com/)

2. [Aleksandrs Ecins](http://www.umiacs.umd.edu/~aecins/)

## License

TextureClassification_FilterBank is released under the BSD 2-Clause license. The code is released for unrestricted use.