1. A Gimp Plugin that uses “GrabCut” to perform image segmentation
Project Proposal and Overview
By: Matthew Marsh

2. What is Image Segmentation?
Divides an image into parts
Easy for humans
Non Trivial for Computers
3 Types of Segmentation
Thresholding
Edge Based
Region Based

3. An Alpha Matte All Segmentation Techniques Create an alpha matte
This is just a labeling of pixels
Some methods allow an alpha value between 0 and 1
Alpha Matte Created After Segmentation
Origional Image

4. Previous Approaches to Segmentation
Magic Wand
User specifies point
Segmentation based on variable tolerance level of color statistics.
Intelligent Scissors
User Draws minimum cost contour
Various seed points
Not effective for highly textured areas e.g long strands of hair

5. “GrabCut” Innovative – uses region and edge information
Also performs border matting
Based upon graph cut

6. Graph cut For greyscale images
Cost function which depends on Edge and Region Information
Minimize cost function to obtain best cut
Cost function in minimized by a Max Flow Algorithm

7. How Graph Cut Works To perform segmentation the user provides ‘seeds’
Pixels labeled as definitely background or foreground (Hard constraints)
Cost function defined by boundary and rejoin properties (Soft constraints)
Cutting along the path of least cost produces best segmentation

8. Graph cut

9. How “GrabCut” extends graph cut
Uses GMMs to work with colour images
Alows an iterative approach to segmentation
Adds Border Matting

10. “GrabCuts” Interactive Approach to Segmentation
Initial Selection
Refinement
Final Segmentation

11. My Project A Gimp Plugin Using “GrabCut” Initial Simplifications:
Use Graph cut approach
No Max flow algorithm
Later Add:
Max flow algorithm
Color functionality using GMMS
Border matting