# Efficient-Graph-Based-Image-Segmentation-Reproduce

**Repository Path**: Sofan_He/efficient-graph-based-image-segmentation-reproduce

## Basic Information

- **Project Name**: Efficient-Graph-Based-Image-Segmentation-Reproduce
- **Description**: 复现经典论文"Efficient Graph-Based Image Segmentation", 附带其官方网站的代码 http://cs.brown.edu/people/pfelzens/segment/
- **Primary Language**: C++
- **License**: GPL-2.0
- **Default Branch**: master
- **Homepage**: http://cs.brown.edu/people/pfelzens/segment/
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2022-04-10
- **Last Updated**: 2023-07-17

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README


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 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.