DocumentCode :
2173178
Title :
Edit distance from graph spectra
Author :
Robles-Kelly, A. ; Hancock, E.R.
Author_Institution :
Dept. of Comput. Sci., York Univ., UK
fYear :
2003
fDate :
13-16 Oct. 2003
Firstpage :
234
Abstract :
We are concerned with computing graph edit distance. One of the criticisms that can be leveled at existing methods for computing graph edit distance is that it lacks the formality and rigour of the computation of string edit distance. Hence, our aim is to convert graphs to string sequences so that standard string edit distance techniques can be used. To do this we use graph spectral seriation method to convert the adjacency matrix into a string or sequence order. We pose the problem of graph-matching as maximum a posteriori probability alignment of the seriation sequences for pairs of graphs. This treatment leads to an expression for the edit costs. We compute the edit distance by finding the sequence of string edit operations, which minimise the cost of the path traversing the edit lattice. The edit costs are defined in terms of the a posteriori probability of visiting a site on the lattice. We demonstrate the method with results on a data-set of Delaunay graphs.
Keywords :
graph theory; image segmentation; pattern matching; tree searching; Delaunay graph data-set; adjacency matrix; graph edit distance computing; graph spectral seriation method; graph-matching problem; posteriori probability alignment; search problems; string sequence; Computer science; Costs; Focusing; Graph theory; Image segmentation; Lattices; Matrix converters; Noise robustness; Sequences; Simulated annealing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on
Conference_Location :
Nice, France
Print_ISBN :
0-7695-1950-4
Type :
conf
DOI :
10.1109/ICCV.2003.1238347
Filename :
1238347
Link To Document :
بازگشت