An Evolutionary-Neural Algorithm for Solving Inverse IFS Problem for Images in Two-Dimensional Space

  • Marzena Bielecka
  • Andrzej Bielecki
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7594)


In this paper an approach based on hybrid, evolutionary-neural computations to the IFS inverse problem is presented. Having a bitmap image we look for an IFS having the attractor approximating of a given image with a good accuracy. A method using IFSes consisting of a variable number of mappings is proposed. A genom has hierarchical structure. A number of different operators acting on various levels of the genome are introduced. The algorithm described in [7] is aided by multi-layer neural networks. Such improved algorithm is less time consuming.


Contractive Mapping Iterate Function System Proportional Selection Contractive Factor Point Coverage 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Marzena Bielecka
    • 1
  • Andrzej Bielecki
    • 2
  1. 1.Chair of Geoinformatics and Applied Computer ScienceAGH University of Science and TechnologyKrakówPoland
  2. 2.Institute of Computer ScienceJagiellonian UniversityKrakówPoland

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