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Binary Image Registration Using Covariant Gaussian Densities

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Image Analysis and Recognition (ICIAR 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5112))

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Abstract

We consider the estimation of 2D affine transformations aligning a known binary shape and its distorted observation. The classical way to solve this registration problem is to find correspondences between the two images and then compute the transformation parameters from these landmarks. In this paper, we propose a novel approach where the exact transformation is obtained as a least-squares solution of a linear system. The basic idea is to fit a Gaussian density to the shapes which preserves the effect of the unknown transformation. It can also be regarded as a consistent coloring of the shapes yielding two rich functions defined over the two shapes to be matched. The advantage of the proposed solution is that it is fast, easy to implement, works without established correspondences and provides a unique and exact solution regardless of the magnitude of transformation.

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Authors and Affiliations

  1. Department of Image Processing and Computer Graphics, University of Szeged, P. O. Box 652., 6701, Szeged, Hungary

    Csaba Domokos & Zoltan Kato

Authors
  1. Csaba Domokos
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  2. Zoltan Kato
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Aurélio Campilho Mohamed Kamel

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© 2008 Springer-Verlag Berlin Heidelberg

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Domokos, C., Kato, Z. (2008). Binary Image Registration Using Covariant Gaussian Densities. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69812-8_45

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  • DOI: https://doi.org/10.1007/978-3-540-69812-8_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69811-1

  • Online ISBN: 978-3-540-69812-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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