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Decentralized Multi-Agent Algorithm for Translational 2D Image Alignment

  • Tomáš MachálekEmail author
  • Kamila Olševičová
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 183)

Abstract

We present a novel multi-agent algorithm applied to the problem of image alignment. Our method operates with multiple concurrent solutions held by agents who each attempt to reach the lowest error function score by trying to place a segment from a translated image to an unsegmented fixed image. Agents borrow and return segments of the translated image from a shared repository and iteratively suggest and evaluate their particular solutions. Finally, the global solution is determined by clustering of agents’ individual results. Experiments show that our approach provides results of high reliability and performance compared with traditional intensity based registration methods that rely on global optimization of a single error function given by translation of whole image.

Keywords

Particle Swarm Optimization Image Registration Segment Size Image Alignment Video Stabilization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Faculty of Informatics and Management, Dept.of Information TechnologiesUniversity of Hradec KrálovéHradec KrálovéCzech Republic

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