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

4 Citations (Scopus)

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

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.",

keywords = "microscopy, environmental sciences, drinking water, microorganisms",

author = "Hernando Fernandez-Canque and Sorin Hintea and Gabor Csipkes and Allan Pellow and Huw Smith",

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

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

TY - GEN

T1 - Machine vision application to the detection of micro-organisms in drinking water

AU - Fernandez-Canque, Hernando

AU - Hintea, Sorin

AU - Csipkes, Gabor

AU - Pellow, Allan

AU - Smith, Huw

N1 - <p>Paper presented at the 12th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, Zagreb, Croatia, 3-5 September 2008. Proceedings ISBN: 9783540855668.</p>

PY - 2008/1/1

Y1 - 2008/1/1

N2 - 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.

AB - 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.

KW - microscopy

KW - environmental sciences

KW - drinking water

KW - microorganisms

U2 - 10.1007/978-3-540-85567-5_38

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

M3 - Conference contribution

SN - 9783540855668

BT - Proceedings of the 12th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems

PB - Springer-Verlag

ER -

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

Abstract

Keywords

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