Water quality analysis: A pattern recognition approach

doi:10.1016/0031-3203(94)00089-5

Pattern Recognition

Volume 28, Issue 2, February 1995, Pages 269-281

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Abstract

The development of a microcomputer-based system for the automatic counting of colonies of indicator organisms (that is, bacteria whose presence is indicative of the presence of pathogens) trapped on membrane filters from water samples is described here. Three different approaches, based on mathematical morphology, distance transform and fuzzy c-means clustering respectively, are implemented and their relative performances are discussed here.

References (7)

S.R. Sternberg
Grayscale morphology
Comput. Vision, Graphics Image Process.
(1986)
Health criteria and epidemiological studies related to coastal water pollution
M.J. Pelczar et al.
Microbiology
(1983)

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^☆: The work has been partially supported by DoE/UNDP (IND/85/072).

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Water quality analysis: A pattern recognition approach☆

Abstract

Comput. Vision, Graphics Image Process.

Microbiology