Graph Based Representations in Pattern Recognition (eBook, PDF)

4th IAPR International Workshop, GbRPR 2003, York, UK, June 30 - July 2, 2003. Proceedings
Redaktion: Hancock, Edwin; Vento, Mario

• Format: PDF

Produktbeschreibung

The refereed proceedings of the 4th IAPR International Workshop on Graph-Based Representation in Pattern Recognition, GbRPR 2003, held in York, UK in June/July 2003.

The 23 revised full papers presented were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on data structures and representation, segmentation, graph edit distance, graph matching, matrix methods, and graph clustering.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 276
• Erscheinungstermin: 1. Januar 2003
• Englisch
• ISBN-13: 9783540450283
• Artikelnr.: 53139490

Autorenporträt

Edwin Hancock, University of New York, NY, USA / Mario Vento, University of Salerno, Italy

Inhaltsangabe

Data Structures and Representation.- Construction of Combinatorial Pyramids.- On Graphs with Unique Node Labels.- Constructing Stochastic Pyramids by MIDES - Maximal Independent Directed Edge Set.- Segmentation.- Functional Modeling of Structured Images.- Building of Symbolic Hierarchical Graphs for Feature Extraction.- Comparison and Convergence of Two Topological Models for 3D Image Segmentation.- Graph Edit Distance.- Tree Edit Distance from Information Theory.- Self-Organizing Graph Edit Distance.- Graph Edit Distance with Node Splitting and Merging, and Its Application to Diatom Identification.- Graph Matching.- Orthonormal Kernel Kronecker Product Graph Mdatching.- Theoretical Analysis and Experimental Comparison of Graph Matching Algorithms for Database Filtering.- A Comparison of Three Maximum Common Subgraph Algorithms on a Large Database of Labeled Graphs.- Swap Strategies for Graph Matching.- Matrix Methods.- Graph Matching Using Spectral Seriation and String Edit Distance.- Graph Polynomials, Principal Pivoting, and Maximum Independent Sets.- Graph Partition for Matching.- Graph Clustering.- Spectral Clustering of Graphs.- Comparison of Distance Measures for Graph-Based Clustering of Documents.- Some Experiments on Clustering a Set of Strings.- A New Median Graph Algorithm.- Graph Clustering Using the Weighted Minimum Common Supergraph.- ACM Attributed Graph Clustering for Learning Classes of Images.- A Competitive Winner-Takes-All Architecture for Classification and Pattern Recognition of Structures.