![[2509.00479] A Novel Method to Determine Total Oxidant Concentration Produced by Non-Thermal Plasma Based on Image Processing and Machine Learning](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
[2509.00479] A Novel Method to Determine Total Oxidant Concentration Produced by Non-Thermal Plasma Based on Image Processing and Machine Learning
Summary
This article presents a novel method for accurately determining total oxidant concentration in non-thermal plasma systems using image processing and machine learning techniques.
Why It Matters
The ability to accurately measure oxidant concentrations is crucial for various applications in environmental science and industrial processes. This study enhances measurement precision by integrating advanced image analysis with machine learning, potentially leading to improved outcomes in plasma treatment technologies.
Key Takeaways
- Introduces a color-based computer analysis method for oxidant measurement.
- Achieves high predictive accuracy (R2 > 0.998) using machine learning models.
- Demonstrates the effectiveness of dimensionality reduction in feature selection.
Electrical Engineering and Systems Science > Image and Video Processing arXiv:2509.00479 (eess) [Submitted on 30 Aug 2025 (v1), last revised 20 Feb 2026 (this version, v2)] Title:A Novel Method to Determine Total Oxidant Concentration Produced by Non-Thermal Plasma Based on Image Processing and Machine Learning Authors:Mirkan Emir Sancak, Unal Sen, Ulker Diler Keris-Sen View a PDF of the paper titled A Novel Method to Determine Total Oxidant Concentration Produced by Non-Thermal Plasma Based on Image Processing and Machine Learning, by Mirkan Emir Sancak and 2 other authors View PDF HTML (experimental) Abstract:Accurate determination of total oxidant concentration [Ox]tot in nonthermal plasma treated aqueous systems remains a critical challenge due to the transient nature of reactive oxygen and nitrogen species and the subjectivity of conventional titration methods used for [Ox]tot determination. This study introduces a color based computer analysis method that integrates advanced image processing with machine learning to quantify colorimetric changes in potassium iodide solutions during oxidation. A custom built visual acquisition system recorded high resolution video of the color transitions occurring during plasma treatment while the change in oxidant concentration was simultaneously monitored using a standard titrimetric method. Extracted image frames were processed through a structured pipeline to obtain RGB, HSV, and Lab color features. Statistical analysis revealed ...