EurOCEAN 2000 - Vlaams Instituut voor de Zee

PROJECT METHODOLOGY
The project is split into three major sections, software development, specimen treatment and
image database. Each is described in overview below.
SOFTWARE DEVELOPMENT
The DiCANN system is essentially software running on a personal computer. The development
of DiCANN will follow standard soft-systems practices, which include rapid prototyping.
DiCANN is being written in C++. It is expected that a series of software releases will take
place during the life of the project. Each will be installed at marine laboratories within the
consortium and users trained in DiCANN operations. Marine Ecologists will therefore be
controlling the training and testing phases of DiCANN. How DiCANN is used and how it
performs will be continuously monitored by the software development team. Releases of
DiCANN will incorporate bug fixes and performance enhancements.
%
performance
100
No. species
Fig. 2 Best mean performance of classifiers
Legend:
BPN = back-propagation of error feed forward Perceptron,
kNN = k-nearest neighbour statistic,
RBF = radial basis function network,
QDA = quadratic discriminant analysis statistic
90
80
70
60
50
4 5 9 14 23
86%
83%
65%
60%
56%
Key:
(classifier type)
BPN
kNN
RBF
QDA
Human
SPECIMEN TREATMENT
Specimen images are taken using calibrated microscopes and 1:1 aspect ratio video cameras.
The preferred fixative methods and specimen handling regimes are being evaluated by this
consortium, to maximise the quality of computer photomicrographs taken of the specimens for
the DiCANN system. Images are stored in an Internet database for access by all project
partners. DiCANN will be trained on many hundreds of examples drawn from this database. Its
performance as an intelligent cell counter of dinoflagellate specimens will be monitored during
extended laboratory trials. Two main types of trial will be run, i) on specimens of Dinophysis
cell cycle and ii) on routine HAB sampling from the Gulf of Trieste.
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