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Robust Keypoint Detection Using Dynamics

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Mathematical Morphology and Its Applications to Signal and Image Processing (ISMM 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7883))

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Abstract

In this paper we present a keypoint detector based on the bimodality of the histograms of oriented gradients (HOGs). We compute the bimodality of each HOG, and a bimodality image is constructed from the result of this bimodality test. The maxima with highest dynamics of the image obtained are selected as robust keypoints. The bimodality test of HOGs used is also based on dynamics. We compare the results obtained using this method with a set of well-known keypoint detectors.

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Author information

Authors and Affiliations

  1. Pontificia Universidad Catolica del Peru, Peru

    Miguel Angel Cataño

  2. Barcelona Tech, Universitat Politecnica de Catalunya, Spain

    Juan Climent

Authors
  1. Miguel Angel Cataño
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  2. Juan Climent
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Editor information

Editors and Affiliations

  1. Centre for Image Analysis, Swedish University of Agricultural Sciences and Uppsala University, Box 337, 751 05, Uppsala, Sweden

    Cris L. Luengo Hendriks , Gunilla Borgefors  & Robin Strand ,  & 

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Cataño, M.A., Climent, J. (2013). Robust Keypoint Detection Using Dynamics. In: Hendriks, C.L.L., Borgefors, G., Strand, R. (eds) Mathematical Morphology and Its Applications to Signal and Image Processing. ISMM 2013. Lecture Notes in Computer Science, vol 7883. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38294-9_34

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  • DOI: https://doi.org/10.1007/978-3-642-38294-9_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38293-2

  • Online ISBN: 978-3-642-38294-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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