• DocumentCode
    457154
  • Title

    A Low-Complexity Deformation Invariant Descriptor

  • Author

    Li Tian ; Kamata, Sei-ichiro

  • Author_Institution
    Graduate Sch. of Info., Waseda Univ., Kitakyushu
  • Volume
    2
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    227
  • Lastpage
    230
  • Abstract
    In this paper, we propose a descriptor which is invariant to general deformations (only intensity locations change but not their value) by using Hilbert scanning. In our method, an image is converted to a 1D sequence through Hilbert scanning at first. Then, we embed this sequence as a 1D curve in the 2D space. Because Hilbert scanning preserves the coherence in a 2D image, it is easily to understand that the area under the curve is invariant to intensity location changes, naturally. Hence, we use some areas for an interest point as a deformation invariant descriptor. This descriptor can be computed in the 2D space efficiently than other approaches where an image is embedded in the 3D space or the dimensions of descriptors are very large. The experimental results show that our descriptor is low-complexity and superior to other approaches on interest point matching in deformation images
  • Keywords
    image matching; image morphing; Hilbert scanning; intensity location changes; interest point matching; low-complexity deformation invariant descriptor; Computational complexity; Data analysis; Embedded computing; Hilbert space; Image coding; Image converters; Image matching; Image retrieval; Image sampling; Object recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.91
  • Filename
    1699188