Title :
Statistical signal modeling techniques for automated recognition of water-borne microbial shapes
Author :
Das, Mangal ; Butterworth, F. ; Das, R.
Author_Institution :
Dept. of Electr. & Syst. Eng., Oakland Univ., Rochester, MI, USA
Abstract :
The purpose of this paper is to present some preliminary results related to the problem of automated detection and identification of water-borne microbiota (bacteria, algae, and protozoa). The topics addressed include acquisition and creation of a microbiota image database, enhancement using Wiener/nonlinear filters, statistical modeling of shape contours, and classification
Keywords :
Wiener filters; biology computing; image classification; image enhancement; modelling; nonlinear filters; statistical analysis; algae; automated detection; automated recognition; bacteria; identification; microbiota image database; protozoa; statistical signal modeling techniques; water-borne microbial shapes; Algae; Background noise; Image databases; Microorganisms; Microscopy; Organisms; Pattern recognition; Shape; Water pollution; Wiener filter;
Conference_Titel :
Circuits and Systems, 1996., IEEE 39th Midwest symposium on
Conference_Location :
Ames, IA
Print_ISBN :
0-7803-3636-4
DOI :
10.1109/MWSCAS.1996.587802
