Applied Mathematics & Information Sciences

Author Country (or Countries)



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%.

Digital Object Identifier (DOI)