Note

Click here to download the full example code

# Region Boundary based RAGsΒΆ

Construct a region boundary RAG with the `rag_boundary`

function. The
function `skimage.future.graph.rag_boundary()`

takes an
`edge_map`

argument, which gives the significance of a feature (such as
edges) being present at each pixel. In a region boundary RAG, the edge weight
between two regions is the average value of the corresponding pixels in
`edge_map`

along their shared boundary.

```
from skimage.future import graph
from skimage import data, segmentation, color, filters, io
from matplotlib import pyplot as plt
img = data.coffee()
gimg = color.rgb2gray(img)
labels = segmentation.slic(img, compactness=30, n_segments=400)
edges = filters.sobel(gimg)
edges_rgb = color.gray2rgb(edges)
g = graph.rag_boundary(labels, edges)
lc = graph.show_rag(labels, g, edges_rgb, img_cmap=None, edge_cmap='viridis',
edge_width=1.2)
plt.colorbar(lc, fraction=0.03)
io.show()
```

**Total running time of the script:** ( 0 minutes 0.803 seconds)