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+# A matlab wrapper for unsupervised segmentation of images based on Felzenszwalb and Huttenlocher
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+
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+## Matlab aspects
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+
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+### Compilation
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+simply run
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+```
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+compileFelzenszwalbSegmentation.m
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+```
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+
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+### Demo
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+1) Run
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+```
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+demoFelzenszwalbSegmentation.m
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+```
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+which requires Matlabs GUI to show images and segmentation results
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+
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+2) Inspect the demo file to learn how to setup variables, and how to call the underlying mex functions
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+
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+## C++ aspects
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+
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+Implementation of the segmentation algorithm described in:
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+
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+*Efficient Graph-Based Image Segmentation
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+Pedro F. Felzenszwalb and Daniel P. Huttenlocher
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+International Journal of Computer Vision, 59(2) September 2004.*
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+
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+The program [segment.cpp, note by A. Freytag] takes a color image (PPM format) and produces a segmentation
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+with a random color assigned to each region.
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+
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+1) Type ```make``` to compile ```segment.cpp```
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+
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+2) Run ```segment sigma k min input output```.
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+
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+The parameters are: (see the paper for details)
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+
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+- sigma: Used to smooth the input image before segmenting it.
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+- k: Value for the threshold function.
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+- min: Minimum component size enforced by post-processing.
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+- input: Input image.
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+- output: Output image.
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+
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+Typical parameters are sigma = 0.5, k = 500, min = 20.
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+Larger values for k result in larger components in the result.
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+
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+
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+NOTE ( by Alexander Freytag )
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+ - only images with less then std::numeric_limits<int>::max() pixels are supported properly!
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+
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+
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Alexander Freytag