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Automatic diatom identification using contour analysis by morphological curvature scale spaces

Lookup NU author(s): Emeritus Professor Steve Juggins

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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. © Springer-Verlag 2005.

Publication metadata

Author(s): Jalba A, Wilkinson M, Roerdink J, Bayer M, Juggins S

Publication type: Article

Publication status: Published

Journal: Machine Vision and Applications

Year: 2005

Volume: 16

Issue: 4

Pages: 217-228

Print publication date: 01/09/2005

ISSN (print): 0932-8092

ISSN (electronic): 1432-1769

URL: http://dx.doi.org/10.1007/s00138-005-0175-8

DOI: 10.1007/s00138-005-0175-8

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