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Multiscale Shape Description with Laplacian Profile and Fourier Transform

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Image Analysis and Recognition (ICIAR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8814))

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Abstract

We propose a new local multiscale image descriptor of variable size. The descriptor combines Laplacian of Gaussian values at different scales with a Radial Fourier Transform. This descriptor provides a compact description of the appearance of a local neighborhood in a manner that is robust to changes in scale and orientation. We evaluate this descriptor by measuring repeatability and recall against 1-precision with the Affine Covariant Features benchmark dataset and as well as with a set of textureless images from the MIRFLICKR Retrieval Evaluation dataset. Experiments reveal performance competitive to the state of the art, while providing a more compact representation.

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Correspondence to Evanthia Mavridou .

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Mavridou, E., Crowley, J.L., Lux, A. (2014). Multiscale Shape Description with Laplacian Profile and Fourier Transform. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8814. Springer, Cham. https://doi.org/10.1007/978-3-319-11758-4_6

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  • DOI: https://doi.org/10.1007/978-3-319-11758-4_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11757-7

  • Online ISBN: 978-3-319-11758-4

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