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

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

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

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

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

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

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

Graph cut

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

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

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