#!/usr/bin/env python
# coding: utf-8

# In[1]:


get_ipython().run_line_magic('matplotlib', 'inline')
import sys
sys.path.insert(0,'..')
from IPython.display import HTML,Image,SVG,YouTubeVideo
from helpers import header

HTML(header())


# # Region based segmentation
# 
# Because edge based segmentation leave contours not closed, one may be interested in searching for regions.

# ## Region growing
# 
# Starting from one point of the “object” region and recruiting neighbouring pixels.

# ## Split and merge

# In[2]:


Image('http://homepages.ulb.ac.be/~odebeir/data/quadtree.png')


# ### split phase
# one define an homogeneity function
# 
# recursive image split:
# * if image is homogeneous 
#     * return
# * else
#     * split the image into 4 and apply the test on each sub-image
# 
# ### merge phase
# 
# * for each adjacent sub-image
#     * if the two grouped regions satisfies the homogeneity criterion, merge the regions

# In[3]:


Image('http://homepages.ulb.ac.be/~odebeir/data/split_example.png')


# >see also:
# * Split and merge [DIP](../00-Preface/06-References.ipynb#[DIP]) p.461

# ## the watershed transform

# >see also:
# * watershed in the [mathematical morphology section](../05-Morphomathematics/03-The watershed transform.ipynb)

# In[ ]: