What kind of data structures are these? Can someone please point out any links or books where I can read more about them.
+2
A:
An explanation can be found in the paper titled "Recognition of shapes by morphological attributed relational graphs", in the beginning of section "3 Generating the attributed relational graph"
In addition, Doxygen doc on an implementation can be found here:
DVK
2010-04-22 05:37:36
+1
A:
You can also check out this paper. From DVK's answer and that link, it sounds like they're normal graphs, but with "attributes" on the nodes and edges. For example, if you were trying to build an image processor, you might initially construct a graph where each node represents a distinctly colored region (say, a person's face vs. their shirt) and then edges represent visual adjacency (likely, a person's head/neck is adjacent to both their shirt and the background of the image).
Then, you would assign attributes to the graph elements. The attribute for each region (node) could be its predominant color, and the attribute for each edge would be how much of their circumference the respective regions share.
As a different example, you a colored graph with edge weights is a simple example of an attributed graph.
Perhaps I could be more helpful with a little more information about why you're looking into ARGs, since they're defined pretty generally.
Seth Pellegrino
2010-04-30 02:57:19
@Seth: Thanks for your answer. I found reference to ARG's while I was studying algorithms for subgraph isomorphism. How are they relevant in that context?
Bruce
2010-04-30 05:05:26
I'd speculate that there's performance gains to be made by marking the graph in a certain way. I haven't been able to find any papers dealing with how that would happen, though. As far as ARGs go, if the algorithm is associating information with either the nodes or the edges, the algorithm would be using an ARG.
Seth Pellegrino
2010-04-30 16:44:56