Multispectral Household Plastic Classification for Recycling Using a Camera Array

Kossira K, Seiler J, Kaup A (2026)


Publication Type: Journal article

Publication year: 2026

Journal

Book Volume: 2026

Article Number: 66

URI: https://arxiv.org/abs/2608.22531

DOI: 10.1186/s13634-026-01362-8

Open Access Link: https://arxiv.org/abs/2608.22531

Abstract

Plastic pollution has become a persistent problem in natural ecosystems. Driven by insufficient waste management, limited recycling efficiency, and high costs for recycling, plastic waste in the environment poses significant ecological and health risks. Recycling requires accurate identification of polymer types, but existing optical sorting systems often struggle to distinguish common household plastics. In this work, we present a novel classification approach based on a multispectral imaging system consisting of nine cameras equipped with near-infrared bandpass filters. The system is designed to discriminate the seven most common household plastics. From the resulting multispectral images, we extract the spectral fingerprints and derive features such as intensity differences between specific wavelength pairs and their slopes, as well as false-color image representations. A dedicated preprocessing pipeline aligns and normalizes the data before classification. We recorded a multispectral household plastic database (https://github.com/FAU-LMS/MHPM) and trained four different classifiers Gradient Boosting, Extreme Gradient Boosting, Light Gradient Boosting Machine, and CatBoost. The best-performing model achieves a classification accuracy of 86.7%. The computational runtime is 2.603 μ" role="presentation">μs per pixel, enabling efficient processing of high-resolution images. The entire setup is built from off-the-shelf hardware components, which makes replication straightforward and allows direct integration into industrial sorting pipelines.

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How to cite

APA:

Kossira, K., Seiler, J., & Kaup, A. (2026). Multispectral Household Plastic Classification for Recycling Using a Camera Array. EURASIP Journal on Advances in Signal Processing, 2026. https://doi.org/10.1186/s13634-026-01362-8

MLA:

Kossira, Katja, Jürgen Seiler, and André Kaup. "Multispectral Household Plastic Classification for Recycling Using a Camera Array." EURASIP Journal on Advances in Signal Processing 2026 (2026).

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