Automated vs. Manual Counting of Bacterial Colonies Using Hough Circle Transform: A Comparative Study for <i>E. coli, S.aureus</i> , and <i>P.aeruginosa</i>

Bacterial colony enumeration is an essential stage in microbiological research, allowing susceptibility to antibiotics assessment, monitoring of the environment, and clinical diagnostics. This research compares automated bacterial colony counting using the Hough Circle Transform to traditional manual counting methods. Objectives include evaluating counting accuracy and efficiency. This study adopted the image processing approach to colonies of E. coli, S. aureus, and P. aeruginosa. The proposed methodology achieved an overall accuracy of 95% for E. coli, 90% for S. aureus, and 84% for P. aeruginosa, with associated recall values of 95%, 91%, and 86%. The F-measure remained continuously high, ranging between 0.85 and 0.95. Regarding efficiency, manual counting required an average of 70 seconds per plate, while automated counting without and with visual correction took 30 seconds. The study contributes to improving laboratory efficiency, with implications for microbiological diagnostics. Future research is suggested to enhance preprocessing and segmentation techniques.

Publication Details

Journal
Journal of Computer Science
Published
2025-10-01
DOI
https://doi.org/10.3844/jcssp.2025.2312.2322
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
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article

Automated vs. Manual Counting of Bacterial Colonies Using Hough Circle Transform: A Comparative Study for E. coli, S.aureus , and P.aeruginosa

Journal of Computer Science
Cell Image Analysis Techniques
article

Automated vs. Manual Counting of Bacterial Colonies Using Hough Circle Transform: A Comparative Study for E. coli, S.aureus , and P.aeruginosa

article en

Abstract

Bacterial colony enumeration is an essential stage in microbiological research, allowing susceptibility to antibiotics assessment, monitoring of the environment, and clinical diagnostics. This research compares automated bacterial colony counting using the Hough Circle Transform to traditional manual counting methods. Objectives include evaluating counting accuracy and efficiency. This study adopted the image processing approach to colonies of E. coli, S. aureus, and P. aeruginosa. The proposed methodology achieved an overall accuracy of 95% for E. coli, 90% for S. aureus, and 84% for P. aeruginosa, with associated recall values of 95%, 91%, and 86%. The F-measure remained continuously high, ranging between 0.85 and 0.95. Regarding efficiency, manual counting required an average of 70 seconds per plate, while automated counting without and with visual correction took 30 seconds. The study contributes to improving laboratory efficiency, with implications for microbiological diagnostics. Future research is suggested to enhance preprocessing and segmentation techniques.

Journal of Computer ScienceVol. 21(10)
Openalex Percentile: Top 24%
Cell Image Analysis Techniques
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