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- ==================== C++ =================================
- 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".
- 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<int>::max() pixels are supported properly!
- =============== MATLAB ==============
- [Compilation]
- - run compileFelzenszwalbSegmentation.m
- [Demo]
- - run demoFelzenszwalbSegmentation.m (requires matlabs GUI to show images and segmentation results)
- - demo file shows how to setup variables, and how to call the underlying mex functions
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