# Resolution of the inverse problem for iterated function systems using Evolutionary Algorithms

This source preferred by Ari Sarafopoulos

**Authors: **Sarafopoulos, A. and Buxton, B.

**Editors: **Yen, G.G., Lucas, S.M., Fogel, G., Kendall, G., Salomon, R., Zhang, B.-T., Coello, C.A. and Runarsson, T.P.

http://ieeexplore.ieee.org/xpl/RecentCon.jsp?punumber=11108

**Pages:** 1071-1078

**Publisher:** IEEE Press

**Place of Publication:** New York

The resolution of the inverse problem for iterated function systems (IFS) is a problem that has remained open, currently there is no general solution that requires no human interaction and provides optimal results. Here we present a novel approach to the resolution of the general inverse problem for IFS using segmentation of target images in conjuction with an Evolutionary Algorithm that is a Genetic Programming-Evolutionary Strategies hybrid

This data was imported from Scopus:

**Authors: **Sarafopoulos, A. and Buxton, B.

**Pages:** 1071-1078

**ISBN:** 9780780394872

The resolution of the inverse problem for iterated function systems (IFS) is a problem that has remained open, currently there is no general solution that requires no human interaction and provides optimal results. Here we present a novel approach to the resolution of the general inverse problem for IFS using segmentation of target images in conjuction with an Evolutionary Algorithm that is a Genetic Programming-Evolutionary Strategies hybrid. © 2006 IEEE.

This data was imported from Web of Science (Lite):

**Authors: **Sarafopoulos, A., Buxton, B. and IEEE

**Pages:** 1056-+

**ISBN:** 978-0-7803-9487-2