Computerized classification systemfor the identification of soil microorganisms

Michał Kruk , Ryszard Kozera , Stanisław Osowski , Pawel Trzciński , Lidia Sas-Paszt , Beata Sumorok , Boleslaw Borkowski

Abstract

This paper presents the method of soil microorganisms identification from the microscopic digital images. The proposed approach includes: Segmentation of the image, feature generation, selection of the most important features and the final recognition stage applying five different solutions of classifiers. The paper presents and discusses the results concerning the recognition of several most popular soil microorganisms: Bacillus subtilis, Paenibacillus glucanolyticus, Rachnella aquatilis, Scoleobasidium sp., Trichoderma sp., Pseudomonas fluorescens, Bacillus atrophaeus, Azotobacter sp., Streptomyces sp. and other bacterias and fungi. The proposed system enables the recognition of the microorganisms with the accuracy close to 98%.

Author Michał Kruk (FoEE / ITEEMIS) - Warsaw University of Life Science (SGGW)
Michał Kruk,,
- The Institute of the Theory of Electrical Engineering, Measurement and Information Systems
, Ryszard Kozera - [Szkola Glowna Gospodarstwa Wiejskiego]
Ryszard Kozera,,
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, Stanisław Osowski (FoEE / ITEEMIS)
Stanisław Osowski,,
- The Institute of the Theory of Electrical Engineering, Measurement and Information Systems
, Pawel Trzciński - [Research Institute of Horticulture, Skierniewice]
Pawel Trzciński,,
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, Lidia Sas-Paszt - [Research Institute of Horticulture, Skierniewice]
Lidia Sas-Paszt,,
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, Beata Sumorok - [Research Institute of Horticulture, Skierniewice]
Beata Sumorok,,
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, Boleslaw Borkowski - [Szkola Glowna Gospodarstwa Wiejskiego]
Boleslaw Borkowski,,
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Journal seriesApplied Mathematics & Information Sciences, [Applied Mathematics & Information Sciences], ISSN 2325-0399, [1935-0090]
Issue year2016
Vol10
Pages21-31
Publication size in sheets0.5
ASJC Classification1703 Computational Theory and Mathematics; 1706 Computer Science Applications; 2603 Analysis; 2604 Applied Mathematics; 2612 Numerical Analysis
DOIDOI:10.18576/amis/100103
Languageen angielski
Score (nominal)30
Score sourcejournalList
ScoreMinisterial score = 0.0, 29-06-2020, ArticleFromJournal
Ministerial score (2013-2016) = 30.0, 29-06-2020, ArticleFromJournal
Publication indicators Scopus Citations = 4; WoS Citations = 2; Scopus SNIP (Source Normalised Impact per Paper): 2016 = 0.632; WoS Impact Factor: 2013 = 1.232 (2) - 2013=1.204 (5)
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