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Measuring the Shape and Size of Activated Sludge Particles Immobilized in Agar with an Open Source Software Pipeline

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Development of Digital Image Processing as an Innovative Method for Activated Sludge Biomass Quantification.

Hashem Asgharnejad¹, Mohammad-Hossein Sarrafzadeh¹

¹School of Chemical Engineering, College of Engineering, University of Tehran, Tehran, Iran.

Frontiers in Microbiology

|October 12, 2020

Summary

This study introduces a novel image processing technique for quantifying activated sludge biomass. Analyzing blue color intensity in RGB images accurately measures cell concentration in wastewater treatment.

Keywords:

RGB analysis activated sludge biomass quantification cell concentration image processing

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Area of Science:

Environmental Science
Biotechnology
Analytical Chemistry

Background:

Activated sludge is crucial for wastewater treatment.
Accurate biomass monitoring is essential for optimizing activated sludge systems.
Existing methods for biomass quantification can be complex.

Purpose of the Study:

To develop a novel, image-based method for quantifying activated sludge biomass.
To assess the accuracy and reliability of the proposed method.
To explore color space transformations for improved biomass estimation.

Main Methods:

Utilized image processing techniques on macroscopic images of activated sludge.
Employed RGB color analysis to correlate color intensity with cell concentration.
Investigated grayscale conversion and Beer-Lambert law for biomass estimation.

Main Results:

Blue color intensity in RGB images accurately predicts cell concentration (R² = 0.990).
Grayscale conversion provides reliable estimates (R² = 0.99).
An exponential correlation based on Beer-Lambert law shows promise (R² = 0.97).

Conclusions:

Image processing offers a highly accurate and efficient method for activated sludge quantification.
RGB and grayscale analyses provide robust biomass monitoring solutions.
This technique can optimize wastewater treatment plant performance.