Quantitative Analysis and Automatic Counting of Microorganisms Using Image Processing Techniques

Abstract

Microorganisms play critical roles in many fields, including medicine, food, and industrial production. Although the quantitative analysis of these organisms is a fundamental process for scientific research, manual counting through visual observation is a highly time-consuming and subjective process for experts. In this study, an automated counting system based on digital image processing techniques was developed to address the disadvantages of manual counting methods. The study utilized 170 microscopic images obtained from 22 different microfungus species. Two distinct methods based on the Circular Hough Transform (CHT) and morphological operations were tested. The results demonstrated that the CHT method, with a precision value of 0.5, exhibited a high correlation of 0.98 with expert counting.