Special Issue "Automated Analysis and Identification of Phytoplankton Images"
A special issue of Applied Sciences (ISSN 2076-3417).
Deadline for manuscript submissions: closed (28 February 2017)
High resolution images of phytoplankton cells, such as diatoms or desmids, can now be acquired by digital microscopes, which facilitates automating the analysis and identification process of specimens. These algae are useful for monitoring water quality, hence the importance of automating the analysis procedure. The conventional approach has usually consisted of identification and quantification using optical microscopy; however, there is a need for automated recognition techniques for diagnostic tools (networks of environmental monitoring, early warning systems) to facilitate proper management of water resources and decision-making processes. However, manual image analysis of such systems is impractical due to the huge diversity of this group of microalgae and its great morphological plasticity. New image analysis systems offer a potentially advantageous compared to manual methods of counting and identification solution. This Special Issue draws attention for contributions that will help to cover the entire workflow of a bioindicator system from capture, analysis or identification to the determination of quality indices.
Dr. Gabriel Cristobal
Dr. Saúl Blanco Lanza
Dr. Gloria Bueno
Prof. Jan Kybic
Manuscript Submission Information
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- Image Acquisition
- Segmentation, matching, simulation
- Shape analysis
- Live cycle analysis
- Image analysis; Feature extraction
- Discriminant analysis
- Software development for image processing and analysis
- Forensic limnology;
- Applications in the environment and earth sciences, e.g., oil and gas exploration, archaeology