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

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

doi:10.1007/978-3-540-85567-5_38

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 proceeding › Conference 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 language	English
Title of host publication	Proceedings of the 12th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems
Publisher	Springer-Verlag
ISBN (Print)	9783540855668
DOIs	https://doi.org/10.1007/978-3-540-85567-5_38
Publication status	Published - 1 Jan 2008

Keywords

microscopy
environmental sciences
drinking water
microorganisms

Documents and Links

10.1007/978-3-540-85567-5_38

http://researchonline.gcu.ac.uk/sec/308

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Cite this

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title = "Machine vision application to the detection of micro-organisms in drinking water",

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.",

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Machine vision application to the detection of micro-organisms in drinking water. / Fernandez-Canque, Hernando; Hintea, Sorin; Csipkes, Gabor; Pellow, Allan; Smith, Huw.

Proceedings of the 12th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems. Springer-Verlag, 2008.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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