Multidimensional Size Functions for Shape Comparison

@article{Biasotti2008MultidimensionalSF,
  title={Multidimensional Size Functions for Shape Comparison},
  author={S. Biasotti and A. Cerri and P. Frosini and D. Giorgi and C. Landi},
  journal={Journal of Mathematical Imaging and Vision},
  year={2008},
  volume={32},
  pages={161-179}
}
  • S. Biasotti, A. Cerri, +2 authors C. Landi
  • Published 2008
  • Mathematics, Computer Science
  • Journal of Mathematical Imaging and Vision
  • Size Theory has proven to be a useful framework for shape analysis in the context of pattern recognition. Its main tool is a shape descriptor called size function. Size Theory has been mostly developed in the 1-dimensional setting, meaning that shapes are studied with respect to functions, defined on the studied objects, with values in ℝ. The potentialities of the k-dimensional setting, that is using functions with values in ℝk, were not explored until now for lack of an efficient computational… CONTINUE READING
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