Self-adaptive evolutionary image registration using differential evolution and artificial immune systems

  • Authors:
  • José SantamaríA;Sergio Damas;José M. GarcíA-Torres;Oscar CordóN

  • Affiliations:
  • Dept. of Computer Science, University of Jaén, Spain;European Centre for Soft Computing, Mieres, Spain;Dept. of Computer Science and Artificial Intelligence, University of Granada, Spain;European Centre for Soft Computing, Mieres, Spain and Dept. of Computer Science and Artificial Intelligence, University of Granada, Spain and Centro de Investigación en Tecnologías de La ...

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2012

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Abstract

Image registration is present in many computer vision and computer graphics real-world applications. Specifically, it plays a crucial role within the 3D digital model acquisition pipeline, in which the iterative closest point (ICP) algorithm is considered the de facto standard for pair-wise alignment of range images. Nevertheless, the success of ICP depends on several assumptions. A new family of registration techniques have been recently proposed based on evolutionary computation paradigm to solve the common ICP problems. Unlike previous contributions, we propose a novel self-adaptive evolutionary image registration algorithm able to search for the values of both the control and the problem solving parameters to achieve accurate alignments, simultaneously. It combines two different population-based optimization approaches that are concerned with the proper optimization of the control parameters and the image alignments, respectively. The performance of our proposal is compared with several state-of-the-art image registration methods.