Title: Bottomhat kernel analysis based on different shape and size using colonies extraction for counting of bacterial colonies in petri dish

Authors: Fitri Utaminingrum; Abdurrohman Hidayat

Addresses: Faculty of Computer Science (FILKOM), Computer Vision Research Groups, Brawijaya University, Malang, 65145, East Java, Indonesia ' Faculty of Computer Science (FILKOM), Computer Vision Research Groups, Brawijaya University, Malang, 65145, East Java, Indonesia

Abstract: Research involving microorganisms such as bacteria mostly were done in many areas such as health, medicine, biology, chemistry and other particle science. The counting process to calculate the number of bacteria in the petri dish is manually using the colony counter. It is possible to obtain error calculated because of human fatigue, inaccuracy, and neglect. Counting the number of bacterial colonies is one of the crucial steps in microbiology testing. An automatic system counted off the number of microbial colonies by using digital image processing is proposed. The proposed method aims to calculate the number of bacterial colonies more quickly, precisely, and effectively. Comparisons show that the proposed method can provide excellent F-measure with the mean value of F-measure is 93.02%. An embed-ready program is implemented in the embedded system to do the automatic bacterial colony counting. This system could give contribution value to the world of microbiology.

Keywords: bacterial colonies; blob detection; bottom-hat kernel; colony extraction; colony counting; Gaussian filter; greyscale image; microbiology; noise removal; petri dish.

DOI: 10.1504/IJCBDD.2021.117185

International Journal of Computational Biology and Drug Design, 2021 Vol.14 No.3, pp.202 - 216

Received: 10 Feb 2020
Accepted: 25 Dec 2020
Published online: 20 Aug 2021 *

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