Open AccessAutomatic Segmentation and Classification of SEM Images of Bacteria Cells
Author(s) -
Mangala Shetty,
Balasubramani Head
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d9120.118419
Subject(s) - artificial intelligence , bacteria , computer vision , computer science , pattern recognition (psychology) , lactic acid , digital image , segmentation , image segmentation , biological system , image (mathematics) , image processing , biology , genetics
In the field of microbiology, digital image analysis methods are receiving significant attention to automatically interpret images of bacterial cells. An automatic procedure to extract and classify images of lactic acid bacteria (LAB) is presented in this paper. Edge based watershed method with automatically generated markers were used to retain the image information at fine scales. The experiment was conducted on images containing one type of bacteria. The scanning electron microscopic (SEM) images of lactic acid bacteria (LAB) are used in this experiment. The image analysis and classification technique described in this paper is quick and simple to recognize organisms based on their morphological characteristics. The classification results indicate that routine methods for the detection, enumeration and identification of bacteria can be automated with use of direct microscopic methods