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- Title
Advancing Microplastic Detection Technology through Digital Image Processing, Fractal Analysis, and Polynomial Approximation Methods.
- Authors
Campos-Lopez, Maximiliano; Aguilar-Garay, Ricardo; Bonilla-Martínez, Ivonne B; Gomez-Castrejon, Jorge O; Mendoza-Pérez, Jorge A; Reyes-Guzmán, Marco A; Garibay-Febles, Vicente
- Abstract
This article discusses the development of an integrated approach for detecting microplastics in environmental samples. Microplastics are small polymer particles that pose a global threat to the environment. The proposed approach combines digital image processing, fractal dimension analysis, and polynomial approximation methods to accurately identify and characterize microplastic particles. The study also introduces a microscopy prototype that enhances the device's utility in microplastic detection and allows for on-site analysis with high precision. The results indicate that this combined approach improves accuracy in microplastic detection and has the potential for widespread environmental monitoring and assessment. The article concludes by highlighting the need for ongoing optimization and validation of the approach and the development of real-time detection systems.
- Subjects
PATTERN recognition systems; POLYNOMIAL approximation; DIGITAL image processing; CONVOLUTIONAL neural networks; POLLUTANTS
- Publication
Microscopy & Microanalysis, 2024, Vol 30, p1
- ISSN
1431-9276
- Publication type
Article
- DOI
10.1093/mam/ozae044.195