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An Efficient Descriptor Based on Radial Line Integration for Fast Non-invariant Matching and Registration of Microscopy Images

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Advanced Concepts for Intelligent Vision Systems (ACIVS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10617))

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Abstract

Descriptors such as SURF and SIFT contain a framework for handling rotation and scale invariance, which generally is not needed when registration and stitching of images in microscopy is the focus. Instead speed and efficiency are more important factors. We propose a descriptor that performs very well for these criteria, which is based on the idea of radial line integration. The result is a descriptor that outperforms both SURF and SIFT when it comes to speed and the number of inliers, even for rather short descriptors.

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Authors and Affiliations

  1. Department of Information Technology, Uppsala University, Uppsala, Sweden

    Anders Hast & Ida-Maria Sintorn

  2. Vironova AB, Stockholm, Sweden

    Gustaf Kylberg & Ida-Maria Sintorn

Authors
  1. Anders Hast
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  2. Gustaf Kylberg
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  3. Ida-Maria Sintorn
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Corresponding author

Correspondence to Anders Hast .

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Editors and Affiliations

  1. DGA, Paris, France

    Jacques Blanc-Talon

  2. University of Antwerp, Antwerp, Belgium

    Rudi Penne

  3. Ghent University - imec, Ghent, Belgium

    Wilfried Philips

  4. CSIRO Data 61, Canberra, Aust Capital Terr, Australia

    Dan Popescu

  5. University of Antwerp, Wilrijk, Belgium

    Paul Scheunders

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Hast, A., Kylberg, G., Sintorn, IM. (2017). An Efficient Descriptor Based on Radial Line Integration for Fast Non-invariant Matching and Registration of Microscopy Images. In: Blanc-Talon, J., Penne, R., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2017. Lecture Notes in Computer Science(), vol 10617. Springer, Cham. https://doi.org/10.1007/978-3-319-70353-4_61

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  • DOI: https://doi.org/10.1007/978-3-319-70353-4_61

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