xiaochengcike / region-growing-by-cellular-automata

This repo contains python implementation for segmentating uniform textures in images using Cellular Automata based Region Growing. Cellular Automata is a cell state evolution theory based on the states of the neighboring cells. For more details, look README.

RegionGrowingAlgorithm

1. This algorithm is used for object segmentation based on user-chosen seed pixels.
2. This paper describes the method presented in the code.

Requirements

1. This module needs Python 2.x, Numpy, SciPy, datetime

Citations

Please site the work if you are using this.

Vezhnevets, Vladimir, and Vadim Konouchine. "GrowCut: Interactive multi-label ND image segmentation by cellular automata." proc. of Graphicon. Vol. 1. 2005.

Usage

General

$ python rgca.py examples/sample/star-white-clipart.jpg examples/sample/seeds

runs with threshold (-t) of 0.5 and with number of iterations (-i) of 50 as default

From terminals

$ python rgca.py examples/sample/star-white-clipart.jpg examples/sample/seeds -t 0.7 -i 75

reads examples/sample/star-white-clipart.jpg from sample folder with seeds given in an utf-8 encoded file as like examples/sample/seeds with threshold of 0.7 and number of iterations as 75

Seeds are be of assumed format

n1,n2
n3,n4

Run

$ python rgca.py -h

for help regarding arguments to be passed