Machine vision application to the detection of micro-organisms in drinking water

Hernando Fernandez-Canque, Sorin Hintea, Gabor Csipkes, Allan Pellow, Huw Smith

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    The work presented in this paper uses a novel Machine Vision application to detect and identify micro-organism oocysts on drinking water. This new concept of water borne micro-organism detection uses image processing to allow detailed inspection of parasite morphology to nanometre dimensions. The detection results are more reliable than existing manual methods. Combining Normarski Differential Interface Contrast (DIC) and fluorescence microscopy using Fluorescein Isothiocyanate (FITC) and UV filters, the system provides a reliable detection of micro-organisms with a considerable reduction in time, cost and subjectivity over the current labour intensive time consuming manual method.

    Original languageEnglish
    Title of host publicationProceedings of the 12th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems
    PublisherSpringer-Verlag
    ISBN (Print)9783540855668
    DOIs
    Publication statusPublished - 1 Jan 2008

    Keywords

    • microscopy
    • environmental sciences
    • drinking water
    • microorganisms

    Fingerprint Dive into the research topics of 'Machine vision application to the detection of micro-organisms in drinking water'. Together they form a unique fingerprint.

  • Cite this

    Fernandez-Canque, H., Hintea, S., Csipkes, G., Pellow, A., & Smith, H. (2008). Machine vision application to the detection of micro-organisms in drinking water. In Proceedings of the 12th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems Springer-Verlag. https://doi.org/10.1007/978-3-540-85567-5_38