Image Segmentation for Aspergillus, Cladosporium, and Trichoderma Fungus

Abstract

In order to support research in drug development, there is a need to classify fungi based on their genus. The first step in this research is to perform image segmentation on various fungi images. This study compares three segmentation methods with image datasets of microorganisms of fungi species from three genera: Aspergillus, Trichoderma, and Cladosporium. Otsu thresholding, adaptive thresholding, and k-means clustering are the three segmentation methods used. The comparison is evaluated using Dice and Jaccard similarity. The evaluation result shows that the adaptive thresholding method obtained the highest value with an average Jaccard score of 0.6102 and a Dice score of 0.7321. The Otsu thresholding method obtained an average Jaccard and Dice score of 0.3738 and 0.4625. Meanwhile, the k-means clustering method got an average Jaccard and Dice score of 0.2524 and 0.3272.