Matlab_FelzenszwalbSegmentation/README.md

A matlab wrapper for unsupervised segmentation of images based on Felzenszwalb and Huttenlocher

Matlab aspects

Compilation

simply run

compileFelzenszwalbSegmentation.m

Setup - safely add repo to search path

To make Matlab familiar with all relevant paths (there are only 2 currently) go to the root folder and execute

initWorkspaceSegmentation.m


### Demo
1) Run  

demoFelzenszwalbSegmentation.m ```
which requires Matlabs GUI to show images and segmentation results

2) Inspect the demo file to learn how to setup variables, and how to call the underlying mex functions

C++ aspects

Implementation of the segmentation algorithm described in:

Efficient Graph-Based Image Segmentation Pedro F. Felzenszwalb and Daniel P. Huttenlocher International Journal of Computer Vision, 59(2) September 2004.

The program [segment.cpp, note by A. Freytag] takes a color image (PPM format) and produces a segmentation with a random color assigned to each region.

1) Type make to compile segment.cpp

2) Run segment sigma k min input output.

The parameters are: (see the paper for details)

• sigma: Used to smooth the input image before segmenting it.
• k: Value for the threshold function.
• min: Minimum component size enforced by post-processing.
• input: Input image.
• output: Output image.

Typical parameters are sigma = 0.5, k = 500, min = 20. Larger values for k result in larger components in the result.

NOTE ( by Alexander Freytag )

• only images with less then std::numeric_limits::max() pixels are supported properly!