Graph Based Image Segmentation

This repository contains an implementation of the graph-based image segmentation algorithms described in [1] focussing on generating oversegmentations, also referred to as superpixels.

[1] P. F. Felzenswalb and D. P. Huttenlocher.
    Efficient Graph-Based Image Segmentation.
    International Journal of Computer Vision, volume 59, number 2, 2004.

Building

The implementation is based on CMake, OpenCV and Boost. The following steps have been tested on Ubuntu 12.04:

$ sudo apt-get install build-essential
$ sudo apt-get install cmake
$ sudo apt-get install libboost-all-dev

OpenCV can either be installed following these instructions, or using:

$ sudo apt-get install libopencv-dev

With all requirements installed, run:

$ mkdir build
$ cd build
$ cmake ..
$ make

Usage

The provided tool can easily be used as follows (from within the build directory):

# Show a help message.
$ ../bin/refh_cli --help
Allowed options:
  -h [ --help ]            produce help message
  --input arg              folder containing the images to process
  --threshold arg (=20)    constant for threshold function
  --minimum-size arg (=10) minimum component size
  --output arg (=output)   save segmentation as CSV file and contour images
# Oversegment the provided examples:
$ ../bin/refh_cli ../data/ ../output --threshold 255

The latter command will create the output directory containing the oversegmentations as .csv files and visualizations as .png files.

License

Note that the two provided imags are taken from the BSDS500 [2].

[2] P. Arbelaez, M. Maire, C. Fowlkes and J. Malik.
    Contour Detection and Hierarchical Image Segmentation
    IEEE TPAMI, Vol. 33, No. 5, pp. 898-916, May 2011.

Copyright (c) 2016, David Stutz All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

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