A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep...

Area of Science:

• Microbiology
• Biotechnology
• Image Analysis

Background:

• Microorganisms are vital in biotechnology, medicine, and industry.
• Accurate microorganism counting is essential for analyzing biomass and biological activity.
• Traditional manual counting methods are laborious, subjective, and not scalable.

Purpose of the Study:

• To review the development of microorganism counting methods using digital image analysis.
• To summarize and analyze commonly used image processing and segmentation techniques.
• To provide insights into future trends and integrated systems for microorganism counting.

Main Methods:

• Literature review of over 144 papers on microorganism counting.
• Categorization of microorganisms into bacteria and others.
• Summary and analysis of image segmentation and processing methodologies.

Main Results:

• Image analysis significantly improves efficiency over traditional manual counting.
• Various image segmentation techniques are applied for microorganism analysis.
• Common technological points in image processing methods are identified.

Conclusions:

• Digital image analysis presents a more efficient and scalable approach to microorganism counting.
• The review offers guidance for developing integrated microorganism counting systems.
• This work provides a foundation for future research in automated microbial analysis.