Methods of classification of the genera and species of bacteria using decision tree
Authors:
- Anna Plichta
Abstract
This paper presents a computer-based method for recognizing digital images of bacterial cells. It covers automatic recognition of twenty genera and species of bacteria chosen by the author whose original contribution to the work consisted in the decision to conduct the process of recognizing bacteria using the simultaneous analysis of the following physical features of bacterial cells: color, size, shape, number of clusters, cluster shape, as well as density and distribution of the cells. The proposed method may be also used to recognize the microorganisms other than bacteria. In addition, it does not require the use of any specialized equipment. The lack of demand for high infrastructural standards and complementarity with the hardware and software widens the scope of the method’s application in diagnostics, including microbiological diagnostics. The proposed method may be used to identify new genera and species of bacteria, but also other microorganisms that exhibit similar morphological characteristics.
- Record ID
- CUT76e98eaa53334519ad634ab961c7e583
- Publication categories
- ;
- Author
- Journal series
- Journal of Telecommunications and Information Technology, ISSN 1509-4553, e-ISSN 1899-8852
- Issue year
- 2019
- No
- 4
- Pages
- 74-82
- Other elements of collation
- rys.; schem.; tab.; Bibliografia (na s.) - 81-82; Bibliografia (liczba pozycji) - 50; Oznaczenie streszczenia - Abstr.; Numeracja w czasopiśmie - 4
- Keywords in English
- bacterial genera and species, decision tree, pattern recognition
- DOI
- DOI:10.26636/jtit.2019.137419 Opening in a new tab
- URL
- https://www.il-pib.pl/pl/jtit-archive?view=kwartalrok&rok=2019&kwartal=4 Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 40
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUT76e98eaa53334519ad634ab961c7e583/
- URN
urn:pkr-prod:CUT76e98eaa53334519ad634ab961c7e583
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.