Morphological shape description using geometric spectrum on multidimensional binary images

Frank Y. Shih, Christopher C. Pu

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

A useful morphological shape description tool is presented called geometric spectrum or G-spectrum, for quantifying the geometric features on multidimensional binary images. The basis of this tool relies upon the cardinality of a set of non-overlapping segments in an image using morphological operations. The G-spectrum preserves the translation invariance property. With a chosen set of isotropic structuring elements the G-spectrum also preserves the rotation invariance. After the procedure of normalization, the G-spectrum can also preserve the scaling invariance. The properties and proofs of the G-spectrum are discussed.

Original languageEnglish (US)
Pages (from-to)921-927
Number of pages7
JournalPattern Recognition
Volume25
Issue number9
DOIs
StatePublished - Sep 1992

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

Keywords

  • Geometric spectrum
  • Image processing
  • Mathematical morphology
  • Pattern recognition
  • Shape description

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