Cart (Loading....) | Create Account
Close category search window
 

Pattern spaces from graph polynomials

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Wilson, R.C. ; Dept. of Comput. Sci., York Univ., UK ; Hancock, E.R.

Although graph structures have proved useful in high level vision for object recognition and matching, they can prove computationally cumbersome because of the need to establish reliable correspondences between nodes. Hence, standard pattern recognition techniques cannot be easily applied to graphs since feature vectors are not easily constructed. To overcome this problem, we turn to the spectral matrix. We show how the elements of this matrix can be used to construct symmetric polynomials that are permutation invariant. The coefficients of these polynomials can be used as graph-features which can be encoded in a vectorial manner. Hence, the symmetric polynomials lead to a representation which is invariant under node permutations and so represents the graph structure without the need for labelling or correspondence operations. We demonstrate that these features are complete and continuous for 'simple' graphs (those without repeated eigenvalues in their spectrum). The notions of stability and discrimination are discussed, and we present experimental evaluation of these properties. Finally, we show that these graph characterizations can be used to cluster graphs from real datasets.

Published in:

Image Analysis and Processing, 2003.Proceedings. 12th International Conference on

Date of Conference:

17-19 Sept. 2003

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.