Clustering of Approaches to Microbiological Image Enhancement and Classification Based on Buser and Baroni-Urbani's Algorithm and Dragomirescu's Homogeneity

Alexandru-Ionut Petrisor, Liviu Dragomirescu, Alan W. Decho

Abstract


Even though microbial imagery had constantly benefited upon technical developments, the analysis of microbial images did not record the same progress. However, analytical tools had been developed in conjunction with remote sensing imagery, and are available for other fields of study as well. When importing such approaches, it is necessary to understand their detailed functioning in order to envisage eventual problems and improve the correctness and accuracy of results. The paper analyzes several approaches to microbial imagery enhancement, quantification, and classification. Approaches are classified using a numerical taxonomy instrument, i.e. Buser and Baroni-Urbani's algorithm and Dragomirescu's homogeneity. Results indicate the presence of three methodological groups and sustain the usage of the image classification/GIS methods in microbiology and other biological fields

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