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A New Method for Affine Registration of Images and Point Sets

  • Juho Kannala
  • Esa Rahtu
  • Janne Heikkilä
  • Mikko Salo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3540)

Abstract

In this paper we propose a novel method for affine registration of images and point patterns. The method is non-iterative and it directly utilizes the intensity distribution of the images or the spatial distribution of points in the patterns. The method can be used to align images of isolated objects or sets of 2D and 3D points. For Euclidean and similarity transformations the additional contraints can be easily embedded in the algorithm. The main advantage of the proposed method is its efficiency since the computational complexity is only linearly proportional to the number of pixels in the images (or to the number of points in the sets).In the experiments we have compared our method with some other non-feature-based registration methods and investigated its robustness. The experiments show that the proposed method is relatively robust so that it can be applied in practical circumstances.

Keywords

Binary Image Similarity Transformation Grayscale Image Point Pattern Registration Method 
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 2005

Authors and Affiliations

  • Juho Kannala
    • 1
  • Esa Rahtu
    • 1
  • Janne Heikkilä
    • 1
  • Mikko Salo
    • 2
  1. 1.Machine Vision Group, Department of Electrical and Information EngineeringUniversity of OuluFinland
  2. 2.Rolf Nevanlinna Institute, Department of Mathematics and StatisticsUniversity of HelsinkiFinland

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