Automatic Segmentation and Classification of SEM Images of Bacteria Cells
Mangala Shetty1, Balasubramani R.2, Vidya S.M.3
1Mangala Shetty, Assistant Professor, Department of MCA, NMAM Institute of Technology, Nitte.
2Balasubramani R., Professor, EDC Head, Department of Information Science and negineering, NMAM Institute of Technology, Nitte.
3Vidya S.M., Ph.D. in Biotechnology, Kuvempu University, Karnataka. M.Sc. in Biotechnology, 1999-2001, Mysore University, Karnataka.
Manuscript received on November 17., 2019. | Revised Manuscript received on November 24 2019. | Manuscript published on 30 November, 2019. | PP: 12858-12860 | Volume-8 Issue-4, November 2019. | Retrieval Number: D9120118419/2019©BEIESP | DOI: 10.35940/ijrte.D9120.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Image Classification, Bacterial Cell Analysis, Segmentation.
Scope of the Article: Classification.