Machine Vision and Applications

, Volume 16, Issue 4, pp 217–228 | Cite as

Automatic diatom identification using contour analysis by morphological curvature scale spaces

  • Andrei C. Jalba
  • Michael H. F. Wilkinson
  • Jos B. T. M. Roerdink
  • Micha M. Bayer
  • Stephen Juggins
Original Paper

Abstract

A method for automatic identification of diatoms (single-celled algae with silica shells) based on extraction of features on the contour of the cells by multi-scale mathematical morphology is presented. After extracting the contour of the cell, it is smoothed adaptively, encoded using Freeman chain code, and converted into a curvature representation which is invariant under translation and scale change. A curvature scale space is built from these data, and the most important features are extracted from it by unsupervised cluster analysis. The resulting pattern vectors, which are also rotation-invariant, provide the input for automatic identification of diatoms by decision trees and k-nearest neighbor classifiers. The method is tested on two large sets of diatom images. The techniques used are applicable to other shapes besides diatoms.

Keywords

Diatom identification Mathematical morphology Contour analysis Curvature scale spaces Multi-scale analysis Decision trees 

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Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  • Andrei C. Jalba
    • 1
  • Michael H. F. Wilkinson
    • 1
  • Jos B. T. M. Roerdink
    • 1
  • Micha M. Bayer
    • 2
  • Stephen Juggins
    • 3
  1. 1.Institute for Mathematics and Computing ScienceUniversity of GroningenGroningenThe Netherlands
  2. 2.Royal Botanic Garden EdinburghScotlandUK
  3. 3.University of Newcastle upon TyneUK

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