A simple image analysis algorithm for evaluation of extended filaments length based on the enhanced digitized image

Area of Science:

• Environmental Science
• Microbiology
• Water Treatment Engineering

Background:

• Activated sludge settling is crucial for wastewater treatment efficiency.
• Filamentous bulking negatively impacts sludge settling and treatment performance.
• Traditional methods for assessing sludge settling can be time-consuming and subjective.

Purpose of the Study:

• To develop an automated image analysis procedure for quantifying activated sludge characteristics.
• To evaluate the settling properties of activated sludge, particularly in cases of filamentous bulking.
• To establish a correlation between image analysis parameters and traditional settling indicators.

Main Methods:

• Developed an automated image analysis algorithm for determining extended filament length and floc area.
• Utilized digitized images from Gram staining for clear segmentation.
• Induced filamentous bulking in a laboratory bioreactor and analyzed sludge samples using image analysis and traditional settling tests.

Main Results:

• The image analysis procedure was accurate and efficient, requiring only 1 minute per image.
• A strong linear relationship was observed between the Diluted Sludge Volume Index (DSVI) and extended filament length.
• Similar linear correlations were found between DSVI and extended filaments per floc area.

Conclusions:

• The developed image analysis algorithm effectively estimates extended filament length and evaluates activated sludge settling characteristics.
• This automated method provides a more accurate and less time-consuming approach compared to traditional techniques.
• The findings support the use of image analysis for monitoring and managing filamentous bulking in wastewater treatment.