Transformation-invariant recursive subdivision method for shape analysis

Qiuming Zhu, Lay kheng Poh

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

3 Scopus citations

Abstract

A method is presented for shape analysis by recursive subdivisions. The subdivisions are invariant with respect to translation, scaling, rotation, and intensity shifting. Eigenvectors of the second central moments are used to derive such subdivisions. A hierarchical shape description uses the invariants defined on the second central moments of the subdivisions. The approach emphasizes the local feature for recognizing object shapes as similar.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Pattern Recognition
PublisherPubl by IEEE
Pages833-835
Number of pages3
ISBN (Print)0818608781
StatePublished - 1988

Publication series

NameProceedings - International Conference on Pattern Recognition

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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  • Cite this

    Zhu, Q., & Poh, L. K. (1988). Transformation-invariant recursive subdivision method for shape analysis. In Proceedings - International Conference on Pattern Recognition (pp. 833-835). (Proceedings - International Conference on Pattern Recognition). Publ by IEEE.