Inexact Graph Retrieval
نویسندگان
چکیده
This paper describes a graph-matching technique for recognising line-pattern shapes in large image databases. We use a Bayesian matching algorithm that draws on edge-consistency and node attribute similarity. This information is used to determine the a posteriori probability of a query graph for each of the candidate matches in the data-base. The node featurevectors are constructed by computing normalised histograms of pairwise geometric attributes. Attribute similarity is assessed by computing the Bhattacharyya distance between the histograms. Recognition is realised by selecting the candidate from the data-base which has the largest a posteriori probability.
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