| dc.creator |
Karatepe, Fatih |
|
| dc.creator |
KAHRİMAN, Mesud |
|
| dc.creator |
COŞKUN, Özlem |
|
| dc.creator |
Tas, Busra |
|
| dc.date |
2022-01-01T00:00:00Z |
|
| dc.date.accessioned |
2023-01-09T12:03:55Z |
|
| dc.date.available |
2023-01-09T12:03:55Z |
|
| dc.identifier |
6e4abf49-0eec-466d-8e33-977bfbe7641e |
|
| dc.identifier |
10.46300/91011.2022.16.31 |
|
| dc.identifier |
https://avesis.sdu.edu.tr/publication/details/6e4abf49-0eec-466d-8e33-977bfbe7641e/oai |
|
| dc.identifier.uri |
http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/97974 |
|
| dc.description |
© 2022 North Atlantic University Union NAUN. All rights reserved.Recently, image processing has proven itself as a fast and reliable technique in research in medicine and biology. Bacterial colony separation is an important and time-consuming process in studies in the field of microbiology. Bacteria counting is usually carried out by the naked eye or even by Coulter counter machines, which are based on the rather expensive electric field measurement method. In this study, image-based enumeration of Escherichia Coli over the colony morphology in the petri dish was investigated. In the experimental study, 4 different bacteria from the Enterobacteriaceae family were planted on petri dishes containing Eosin-methylene blue agar (Merck, Darmstadt, Germany). Escherichia Coli colony characteristics were determined by digitizing planted bacterial petri images. For the study, counting was done with the interface developed in MATLAB R2013a. After the classification criteria were determined, the method was tested on new petri dishes and successful results were obtained. |
|
| dc.language |
eng |
|
| dc.rights |
info:eu-repo/semantics/openAccess |
|
| dc.title |
Detection of Escherichia Coli Bacteria by Using Image Processing Techniques |
|
| dc.type |
info:eu-repo/semantics/article |
|