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Fuzzy Computer Vision Toolbox

Release on July 05, 2017


A toolbox for Fuzzy Computer Vision. This is part of the tutorial that is going to be presented in FUZZ-IEEE 2017, Naples, Italy, as well as the implementation of our TFS work with titled Scene Image is Non-Mutually Exclusive - A Fuzzy Qualitative Scene Understanding.

There are a few prerequisites before you start this practical, please ensure you have installed the following toolboxes or libraries in your computer. You may follow the steps below for installation:

  1. Install Python (Recommend Anaconda Python 2.7 version)

  2. Install opencv library (version 2.4.x.x)

    1. Download opencv library from:
    2. Double-click to extract the opencv.
    3. Go to “opencv/build/python/2.7/x64 folder.”
    4. Copy cv2.pyd to your python directory in the “lib/site-packages”.
  3. Install scikit-image package.

    1. Open anaconda prompt
    2. Type “pip install scikit-image”
    3. Web reference:
  4. Install scikit-learn package.

    1. Open anaconda prompt
    2. Type “pip install scikit-learn”
    3. Web reference:



If you find this code useful for your research, please cite

  author    = {Chern Hong Lim and Anhar Risnumawan and Chee Seng Chan},
  title     = {Scene Image is Non-Mutually Exclusive - {A} Fuzzy Qualitative Scene Understanding},
  journal   = {{IEEE} Trans. Fuzzy Systems},
  volume    = {22},
  number    = {6},
  pages     = {1541--1556},
  year      = {2014},
  url       = {},
  doi       = {10.1109/TFUZZ.2014.2298233},


Suggestions and opinions of this work (both positive and negative) are greatly welcome. Please contact the authors by sending email to Chern Hong Lim at chlim at or Chee Seng Chan at cs.chan at


BSD-3, see LICENSE file for details.