Overview
- Will serve as a foundation for a variety of useful applications of the graph theory to computer vision, pattern recognition, and related areas
- Covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 52)
Buy print copy
About this book
Similar content being viewed by others
Keywords
Table of contents (10 chapters)
-
Applied Graph Theory for Low Level Image Processing and Segmentation
-
Graph Similarity, Matching, and Learning for High Level Computer Vision and Pattern Recognition
Editors and Affiliations
Bibliographic Information
Book Title: Applied Graph Theory in Computer Vision and Pattern Recognition
Editors: Abraham Kandel, Horst Bunke, Mark Last
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-68020-8
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2007
Hardcover ISBN: 978-3-540-68019-2Published: 12 March 2007
Softcover ISBN: 978-3-642-08764-6Published: 13 November 2010
eBook ISBN: 978-3-540-68020-8Published: 11 April 2007
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: X, 266
Topics: Mathematical and Computational Engineering, Artificial Intelligence