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Material analysis with polarization holography and machine learning
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Researchers developed a polarization holographic imaging system combined with machine learning to identify different materials, demonstrating the approach on microplastic identification. This novel optical method could become a fast, non-destructive tool for classifying microplastics in environmental samples.
We design a polarization holographic system to record the sample holographic images with rich polarization states, amplitude, and phase information. Material analysis and characterization are realized with machine learning. We demonstrate the system feasibility on specific microplastic material identification.
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