Morphological recognition with the addition of multi-band fluorescence excitation of chlorophylls of phytoplankton
- 111 Downloads
The recognition of aquatic organisms plays a crucial role in the monitoring of the pollution and for the adoption of rapid preventive actions. A compact microscopic optical imaging system is proposed in order to acquire and treat the multibands fluorescence of several pigments in phytoplankton organisms. Two algorithms for automatic recognition of phytoplankton were proposed with a minimum number of calibration parameters. The first algorithm provides a morphological recognition based on “watershed” segmentation and Fourier descriptors, while the second one builds fluorescence pigment images by “k-means” partition of intensity ratios. The operation of these algorithms was illustrated by the study of two different organisms: a cyanobacteria (Dolichospermum sp.) and an alga (Cladophora sp.). The family and the genus of these organisms were then classified into a database which is independent of the size, the orientation and the position of the specimens in the images.
Additional key wordsaquatic organism fluorescence imaging morphological extraction pigment
charge coupled device
Unable to display preview. Download preview PDF.
This work was supported by Europe (FEDER), Lorraine region and the project “BioCapTech”. The authors wish to thank emeritus Pr. Jean-Claude Pihan and Dr Cécile Dupouy (IRD, Nouméa) for their advices during the course of this study.
- Chen X.: Skin lesion segmentation by an adaptive watershed flooding approach.–PhD Dissertation, Univ. Missouri-Rolla, 2007Google Scholar
- Govindjee Shevela D.: Adventures with Cyanobacteria: a personal perspective.–Front. Plant Sci. 2: 1–17, 2011.Google Scholar
- Guidi L., Degl’Innocenti E.: Imaging of chl a fluorescence: a tool to study abiotic stress in plants.–In: Shanker A., Venkateswarlu B. (ed.): Abiotic Stress in Plants–Mechanisms and Adaptations. Pp. 3–20. In Tech, 2011.Google Scholar
- Hall E. L.: Computer Image Processing and Recognition. Pp. 585. Academic Press, New York 1979.Google Scholar
- Hudnell H. K.: Cyanobacterial Harmful Algal Blooms: State of the Science and Research Needs: State of the Science and Research Needs. Pp. 2–15. Springer Sci. Business Media, New York 2008.Google Scholar
- Komárek J., Anagnostidis K.: [Freshwater Flora of Central Europe: Chroococcales.] Pp. 548. Gustav Fischer Verlag, Stuttgart 2000 [In German]Google Scholar
- Poryvkina L., Babichenko S., Leeben A.: Analysis of phytoplankton pigments by excitation spectra of fluorescence.–EARSeL eProceedings 1: 224–232 2000.Google Scholar
- Rabinowitch E., Govindjee U.: Photosynthesis. Pp. 102–123. John Wiley & Sons, New York 2013.Google Scholar
- Seppälä J., Babichenko S., Leeben A. et al.: Fluorescence diagnostics of phytoplankton bloom in Baltic, Institute of Ecology, Tallinn Estonia.–In: Proceedings of the Six International Conference on Remote Sensing for Marine and Coastal Environments. Pp. 377–383. Environmental Research Institute of Michigan, Ann Arbor 2000.Google Scholar
- van den Hoek C.: Revision of the European Species of Cladophora. Pp. 363. Brill Acad. Publ., Leiden 1963.Google Scholar