This volume contains the papers presented at the Fourth IAPR Workshop on Graph Based Representations in Pattern Recognition. The workshop was held at the King’s Manor in York, England between 30 June and 2nd July 2003. The previous workshops in the series were held in Lyon, France (1997), Haindorf, Austria (1999), and Ischia, Italy (2001). The city of York provided an interesting venue for the meeting. It has been said that the history of York is the history of England. There have been both Roman and Viking episodes. For instance, Constantine was proclaimed emperor in York. The city has also been a major seat of ecclesiastical power and was also involved in the development of the railways in the nineteenth century. Much of York’s history is evidenced by its buildings, and the King’s Manor is one of the most important and attractive of these. Originally part of the Abbey, after the dissolution of the monasteries by Henry VIII, the building became a center of government for the Tudors and the Stuarts (who stayed here regularly on their journeys between London and Edinburgh), serving as the headquarters of the Council of the North until it was disbanded in 1561. The building became part of the University of York at its foundation in 1963. The papers in the workshop span the topics of representation, segmentation, graph-matching, graph edit-distance, matrix and spectral methods, and gra- clustering.
Author(s): Luc Brun, Walter G. Kropatsch (auth.), Edwin Hancock, Mario Vento (eds.)
Series: Lecture Notes in Computer Science 2726
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2003
Language: English
Pages: 276
Tags: Pattern Recognition; Computer Science, general; Data Structures; Discrete Mathematics in Computer Science; Computer Graphics; Image Processing and Computer Vision
Construction of Combinatorial Pyramids....Pages 1-12
On Graphs with Unique Node Labels....Pages 13-23
Constructing Stochastic Pyramids by MIDES — Maximal Independent Directed Edge Set....Pages 24-34
Functional Modeling of Structured Images....Pages 35-46
Building of Symbolic Hierarchical Graphs for Feature Extraction....Pages 47-58
Comparison and Convergence of Two Topological Models for 3D Image Segmentation....Pages 59-70
Tree Edit Distance from Information Theory....Pages 71-82
Self-Organizing Graph Edit Distance....Pages 83-94
Graph Edit Distance with Node Splitting and Merging, and Its Application to Diatom Identification....Pages 95-106
Orthonormal Kernel Kronecker Product Graph Mdatching....Pages 107-117
Theoretical Analysis and Experimental Comparison of Graph Matching Algorithms for Database Filtering....Pages 118-129
A Comparison of Three Maximum Common Subgraph Algorithms on a Large Database of Labeled Graphs....Pages 130-141
Swap Strategies for Graph Matching....Pages 142-153
Graph Matching Using Spectral Seriation and String Edit Distance....Pages 154-165
Graph Polynomials, Principal Pivoting, and Maximum Independent Sets....Pages 166-177
Graph Partition for Matching....Pages 178-189
Spectral Clustering of Graphs....Pages 190-201
Comparison of Distance Measures for Graph-Based Clustering of Documents....Pages 202-213
Some Experiments on Clustering a Set of Strings....Pages 214-224
A New Median Graph Algorithm....Pages 225-234
Graph Clustering Using the Weighted Minimum Common Supergraph....Pages 235-246
ACM Attributed Graph Clustering for Learning Classes of Images....Pages 247-258
A Competitive Winner-Takes-All Architecture for Classification and Pattern Recognition of Structures....Pages 259-270
