DocumentCode
1619126
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
Volume
2
fYear
1996
Firstpage
613
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1996., IEEE 39th Midwest symposium on
Conference_Location
Ames, IA
Print_ISBN
0-7803-3636-4
Type
conf
DOI
10.1109/MWSCAS.1996.587802
Filename
587802
Link To Document