scispace - formally typeset
Journal ArticleDOI

Approximate graph edit distance computation by means of bipartite graph matching

Kaspar Riesen, +1 more
- 01 Jun 2009 - 
- Vol. 27, Iss: 7, pp 950-959
Reads0
Chats0
TLDR
A novel algorithm is introduced which allows us to approximately, or suboptimally, compute edit distance in a substantially faster way and is emprically verified that the accuracy of the suboptimal distance remains sufficiently accurate for various pattern recognition applications.
About
This article is published in Image and Vision Computing.The article was published on 2009-06-01. It has received 654 citations till now. The article focuses on the topics: Graph operations & Line graph.

read more

Citations
More filters
Book ChapterDOI

Fast Graph Similarity Search via Locality Sensitive Hashing

TL;DR: A fast graph search algorithm is proposed, which first transforms complex graphs into vectorial representations based on the prototypes in the database and then accelerates query efficiency in Euclidean space by employing locality sensitive hashing.
Journal ArticleDOI

Improved local search for graph edit distance

TL;DR: K-REFINE generalizes and improves an existing local search algorithm and performs particularly well on small graphs and RANDPOST is a general warm start framework that stochastically generates promising initial solutions to be used by any local search based GED algorithm.
Book ChapterDOI

Extracting plane graphs from images

TL;DR: The technique is introduced, which consists in segmenting the original image, extracting interest pixels on the segmented image, then converting these pixels into pointels, which in turn can be related by region-based triangulation.
Journal ArticleDOI

Error-tolerant geometric graph similarity and matching

TL;DR: The vertex distance (dissimilarity) and edge distance between two geometric graphs and use it to compute graph distance and use graph distance to perform error-tolerant graph matching.
Journal ArticleDOI

Bridging structure and feature representations in graph matching

TL;DR: It is shown that weighted combinations of dissimilarities may perform better than these two extremes, indicating that these two types of information are essentially different and strengthen each other.
References
More filters
Journal ArticleDOI

The Protein Data Bank

TL;DR: The goals of the PDB are described, the systems in place for data deposition and access, how to obtain further information and plans for the future development of the resource are described.
Journal ArticleDOI

The Hungarian method for the assignment problem

TL;DR: This paper has always been one of my favorite children, combining as it does elements of the duality of linear programming and combinatorial tools from graph theory, and it may be of some interest to tell the story of its origin this article.
Journal ArticleDOI

A Formal Basis for the Heuristic Determination of Minimum Cost Paths

TL;DR: How heuristic information from the problem domain can be incorporated into a formal mathematical theory of graph searching is described and an optimality property of a class of search strategies is demonstrated.
Related Papers (5)