Classification of irregularly shaped micro-objects using complex Fourier descriptors

Volodymyr V. Kindratenko, Pierre J.M. Vanespen

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


A new method for characterizing complex irregular shapes of natural objects (e.g. plant cells, aerosol particles) is presented. The method employs complex Fourier analysis rather than the traditional forms of the Fourier analysis. Digitized images of objects are processed and the contours are tracked by a classical boundary following technique. A new contour preprocessing technique allows to normalize position, size and orientation of a contour. A new contour resampling technique results in a more precise polygonal approximation of the contour. The resampled contour is represented in a complex plane and its complex Fourier coefficients are computed. The technique is applied to the classification of individual algae cells and their agglomerates employing two different classification methods: hierarchical clustering and neural network. The results demonstrate the applicability of the method for the classification of complex irregular shapes.

Original languageEnglish (US)
Title of host publicationTrack B
Subtitle of host publicationPattern Recognition and Signal Analysis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Print)081867282X, 9780818672828
StatePublished - 1996
Externally publishedYes
Event13th International Conference on Pattern Recognition, ICPR 1996 - Vienna, Austria
Duration: Aug 25 1996Aug 29 1996

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651


Other13th International Conference on Pattern Recognition, ICPR 1996

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition


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