Description: “GrowCut” - Interactive Multi-Label N-D Image Segmentation By Cellular
Automata
Abstract
In this project we describe a novel algorithm for interactive multilabel
segmentation of N-dimensional images. Given a small number
of user-labelled pixels, the rest of the image is segmented automatically
by a Cellular Automaton. The process is iterative, as
the automaton labels the image, user can observe the segmentation
evolution and guide the algorithm with human input where the segmentation
is difficult to compute. In the areas, where the segmentation
is reliably computed automatically no additional user effort
is required. Results of segmenting generic photos and medical images
are presented. Our experiments show that modest user effort
is required for segmentation of moderately hard images.
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File list (Check if you may need any files):
growcut\growcut.m
.......\growcutmex.cpp
.......\growcutmex.mexglx
.......\growcutmex.mexmaci
.......\growcutmex.mexw32
.......\growcut_test.m
.......\labels.png
.......\lotus.png
growcut
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