Image Feature Detection on Content-Based Meshes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

Abstract

Non-uniformly sampled images represented on irregular content-based meshes are central to the developments in image compression techniques and in efficient motion tracking. We present a general approach to the development of systematic design procedures for scalable and adaptive low level image processing operators that can be applied to such non-uniformly sampled images. We provide algorithms that use the content-based mesh to address the usually difficult issue of local operator scale selection. The operator scale is therefore automatically matched to the local scale of the image features as embodied in the mesh. In this way we are able to apply a range of operators directly to compressed images. We demonstrate the approach with the design of image derivative operators that enable image feature detection to be implemented directly on compressed images.
Original languageEnglish
Title of host publicationUnknown Host Publication
PublisherIEEE Signal Processing Society
PagesI-844-I-847
Number of pages4
Volume1
DOIs
Publication statusPublished - Oct 2002
EventIEEE International Conference on Image Processing (ICIP 2002) - Rochester, New York
Duration: 1 Oct 2002 → …

Conference

ConferenceIEEE International Conference on Image Processing (ICIP 2002)
Period1/10/02 → …

Keywords

  • Fetaure detection
  • content-based meshes
  • non-uniformly sampled images
  • image derivative operators
  • adaptive image operators

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  • Cite this

    Coleman, SA., Scotney, BW., & Herron, MG. (2002). Image Feature Detection on Content-Based Meshes. In Unknown Host Publication (Vol. 1, pp. I-844-I-847). IEEE Signal Processing Society. https://doi.org/10.1109/ICIP.2002.1038157