2004 | OriginalPaper | Chapter
An Error-Tolerant Approximate Matching Algorithm for Attributed Planar Graphs and Its Application to Fingerprint Classification
Authors : Michel Neuhaus, Horst Bunke
Published in: Structural, Syntactic, and Statistical Pattern Recognition
Publisher: Springer Berlin Heidelberg
Included in: Professional Book Archive
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Graph edit distance is a powerful error-tolerant similarity measure for graphs. For pattern recognition problems involving large graphs, however, the high computational complexity makes it sometimes impossible to apply edit distance algorithms. In the present paper we propose an efficient algorithm for edit distance computation of planar graphs. Given graphs embedded in the plane, we iteratively match small subgraphs by locally optimizing structural correspondences. Eventually we obtain a valid edit path and hence an upper bound of the edit distance. To demonstrate the efficiency of our approach, we apply the proposed algorithm to the problem of fingerprint classification.