Modelling life cycle related and individual shape variation in biological specimens

Hicks, Yulia Alexandrovna ORCID: https://orcid.org/0000-0002-7179-4587, Marshall, Andrew David ORCID: https://orcid.org/0000-0003-2789-1395, Rosin, Paul L. ORCID: https://orcid.org/0000-0002-4965-3884, Martin, Ralph Robert, Bayer, Micha M. and Mann, David G. 2002. Modelling life cycle related and individual shape variation in biological specimens. Presented at: 13th British Machine Vision Conference, Cardiff, Wales, 2-5 Sept 2002.

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Abstract

The main purpose of this research is to develop methods for automatic identification of biological specimens in digital photographs and drawings held in a database. Incorporation of taxonomic drawings into a visual indexing system has not been attempted to date. Diatoms are a single cell microscopic algae that provide a particularly suitable case study. Identification of diatoms is a challenging task due to the huge number of the species, blurred boundaries between species, and life cycle related shape changes. A novel model based on principal curves representing the life cycle related shape variation of a number of diatom species has been developed. Our model is suitable for reconstruction purposes, allowing us to produce drawings of a variety of diatom shapes, thus providing a link between the photographs and drawings. We present the classification results of photographed and drawn specimens based on the model and compare our results to another recent system for diatom identification. Finally, given a diatom specimen, we are able not only to identify the species it belongs to but also to pinpoint the stage in the life cycle it represents.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics Engineering
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Uncontrolled Keywords:	Biological specimens ; modelling ; methods for automatic identification ; digital photographs ; image database; diatoms ; biology classification.
Last Modified:	17 Oct 2022 09:40
URI:	https://orca.cardiff.ac.uk/id/eprint/5113

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