Phytoplankton identification by combined methods of morphological processing and fluorescence imaging

Mathieu Lauffer 1 Frédéric Genty 1 Jean-Luc Collette 2 Samuel Margueron 1
1 LMOPS - Laboratoire Matériaux Optiques, Photonique et Systèmes
2 UMI2958 - Georgia Tech - CNRS [Metz]
Abstract : The identification of phytoplankton is currently an important issue to prevent the aquatic environment. The growth of one or several phytoplankton species can lead to hyper eutrophication and causes lethal consequences on other organisms. In this paper, the selective recognition of invading species is investigated by automatic recognition algorithms of optical and fluorescence imaging. Firstly, morphological characteristics of algae of microscopic imaging are treated. The image processing lead to the identification the genus of aquatic organisms and compared to a morphologic data base. Secondly, fluorescence images allow an automatic recognition based on multispectral data that identify locally the ratio of different photosynthetic pigments and gives a unique finger print of algae. It is shown that the combination of both methods are useful in the recognition of aquatic organisms.
Keywords : fluorescence hydrological techniques microorganisms water quality
Type de document :
Communication dans un congrès
EESMS, Jul 2015, Trento, Italy. pp.131-135, Proceedings of IEEE Workshop on Environmental, Energy and Structural Monitoring Systems. 〈10.1109/EESMS.2015.7175865〉
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Contributeur : Sébastien Van Luchene <>
Soumis le : vendredi 11 mars 2016 - 13:18:32
Dernière modification le : jeudi 5 avril 2018 - 12:30:21

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Mathieu Lauffer, Frédéric Genty, Jean-Luc Collette, Samuel Margueron. Phytoplankton identification by combined methods of morphological processing and fluorescence imaging. EESMS, Jul 2015, Trento, Italy. pp.131-135, Proceedings of IEEE Workshop on Environmental, Energy and Structural Monitoring Systems. 〈10.1109/EESMS.2015.7175865〉. 〈hal-01286763〉

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