• DocumentCode
    556712
  • Title

    Automatic unsupervised shape recognition technique using moment invariants

  • Author

    Barbu, Tudor

  • Author_Institution
    Iasi Branch, Inst. of Comput. Sci., Iasi, Romania
  • fYear
    2011
  • fDate
    14-16 Oct. 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    We approach the shape recognition domain in this paper. After an introduction in the image shape analysis domain, we describe a shape feature extraction technique using moment-based measures which are invariant to geometric transforms. Then, an automatic unsupervised feature vector classification approach is proposed. It is based on a sequence of hierarchical agglomerative region-growing clustering algorithms and a measure based on cluster validation indexes. The results of this provided recognition technique can be applied successfully in important domains, such as object recognition, shape-based image content indexing and retrieval.
  • Keywords
    feature extraction; method of moments; pattern classification; shape recognition; transforms; automatic unsupervised feature vector classification approach; automatic unsupervised shape recognition technique; cluster validation indexes; geometric transforms; hierarchical agglomerative region-growing clustering algorithms; image shape analysis domain; moment invariants; moment-based measures; shape feature extraction technique; shape recognition domain; Clustering algorithms; Feature extraction; Image recognition; Indexes; Object recognition; Shape; Support vector machine classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Theory, Control, and Computing (ICSTCC), 2011 15th International Conference on
  • Conference_Location
    Sinaia
  • Print_ISBN
    978-1-4577-1173-2
  • Type

    conf

  • Filename
    6085654