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Conference 13006 > Paper 13006-21
Paper 13006-21

Development of reflection removal methods for automated bacterial colony counting using computer vision technologies (Invited Paper)

9 April 2024 • 10:50 - 11:20 CEST | Etoile B, Niveau/Level 1

Abstract

The problem of automated bacterial colony counting is a very relevant one, due to the high importance of bacteriological analysis. Moreover, this automated counting saves biologists time and improves the accuracy of their experiments. This paper has two aims: to investigate the challenges of automated bacterial colony counting, and to address the joint challenges of petri dish localization and bacterial colony reflections in such dishes. These reflections can seriously reduce the accuracy of automated bacterial colony counting. Therefore, the main aim of this paper is to show new methods for detecting and removing bacterial colony reflections in a petri dish by the use of computer vision. It also proposes new methods for petri dish localization and the digital removal of bacterial colony reflections. Additionally, these methods can be implemented on a mobile platform, such as Android and Raspberry Pi. The experimental part of the paper contains the results, and descriptions of petri dish localization, and detecting and removing bacterial colony reflections. The proposed methods and the data obtained from these experiments significantly improve the accuracy of automated bacterial colony counting.

Presenter

Artjoms Suponenkovs
Riga Technical Univ. (Latvia)
Artjoms Suponenkovs was born on January 3, 1992. He has participated in district and republican programming, mathematics and physics student competitions. Graduated from the programming school "PRGMEISTARS". He received a Bachelor’s (2014), Master’s (2016) and Doctorate (2021) degree in computer science from Riga Technical university. He had graduated with excellence and being included in the “RTU Golden Fund”. His latest research interests are magnetic resonance imaging, automated medical image segmentation, computer vision in manufacturing, FPGA – (field-programmable gate array), intelligent character recognition and traffic sign recognition systems. The latest focus is developing computer vision applications and MS software of various complexities based on the MVC architectural pattern. He has participated in many research projects.
Presenter/Author
Artjoms Suponenkovs
Riga Technical Univ. (Latvia)
Author
Dmitrijs Bliznuks
Riga Technical Univ. (Latvia)
Author
Loughborough Univ. (United Kingdom)
Author
Alexey Lihachev
Univ. of Latvia (Latvia)