Abstract

This document addresses a study that aims to simplify and automate the counting and analysis of biological samples, specifically pathogens cultivated in Petri dishes. The study focuses on the use of computer vision techniques and technologies such as OpenCV, Jetson Nano, 5G, and FSO to achieve this goal. The document explains the methodology used, including color space conversion, thresholding, morphological transformations, and contour detection. It also highlights the challenges and limitations of automated counting methods, as well as the need for validation and standardization. Finally, the document presents the results of the experiment and discusses the potential benefits of the developed system.