• DocumentCode
    419613
  • Title

    Convexity recognition using multi-scale autoconvolution

  • Author

    Rahtu, Esa ; Salo, Mikko ; Heikkilä, Janne

  • Author_Institution
    Dept. of Electr. Eng., Oulu Univ., Finland
  • Volume
    1
  • fYear
    2004
  • fDate
    23-26 Aug. 2004
  • Firstpage
    692
  • Abstract
    This paper introduces a novel measure for object convexity using the recently introduced multi-scale autoconvolution transform. The proposed measure is computationally efficient and recognizes even small errors in a convex domain. We also consider its implementation and give a complete Matlab algorithm for computing this measure for digital images. Finally, we give examples to verify its applicability and accuracy. The examples also consider convexity as a measure for complexity.
  • Keywords
    convolution; image recognition; object recognition; set theory; Matlab algorithm; digital images; multiscale autoconvolution transform; object convexity recognition; Computer vision; Digital images; Electric variables measurement; Image analysis; Machine vision; Mathematics; Noise measurement; Probability density function; Random variables; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2128-2
  • Type

    conf

  • DOI
    10.1109/ICPR.2004.1334271
  • Filename
    1334271