Image Segmentation using Cage Active Contours(CAC). This project provides a complementary open-source code for the published results in the paper Cage Active Contours for image warping and morphing published in EURASIP journal on Image and Video Processing.

0. Requirements Images and ground truth images must be of type .png
1. Creating the initial Contour

The script mask_from_images creates the initial contours given an initial image. To do this it requires:

a) A .txt file with the path of the image or images to segment

b) A .txt file with the path of the ground truth images so that their file names match the images' file names.

c) A .txt file where the initial information will be written to match the input format required for the segmentation.

Once this is done, and mask_from_images is run, images will appear one by one. The user is required to click on the image twice:

a) First, to mark the center of your initial circular contour

b) Second, to mark a point of the radius of your initial circular contour

Now a the input file is obtained to be able to apply the segmentation

2. Running the Segmentation Procedure

   a) Open one of the following classes with the desired energy:

   i) MeanCAC

   ii) OriginalGaussianCAC

   iii) GaussianCAC

   iv) MixtureGaussianCAC

   v) MultivariateGaussianCAC

   vi) MultiMixtureGaussianCAC

   vii) HueMeanCAC

   b) Change the input file with the one generated previously

   c) Run

1. OpenCV

2. Python 2.7

In the main_directory/apicac/ folder, do the following:

clean make

make