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DoFP Polarimetric Microplastic Dataset: Raw and Derived Stokes/AOLP/DOLP Images
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This dataset provides raw and processed polarimetric images of 600 microplastic particles across three polymer types (PP, HDPE, LDPE) captured using a division-of-focal-plane polarization camera, enabling image-based polymer classification. Polarimetric imaging represents a promising non-destructive optical method for rapid, automated identification of colorless microplastic particles in water.
General Information Description: This dataset contains the raw and processed polarization images used for the image-based classification of three common microplastic polymer types (PP, HDPE, LDPE) submerged in water. Data Description and Acquisition The dataset consists of polarization images of 600 colorless, irregularly shaped, and opaque microplastic particles (200 of each polymer type). The particles are 50−300 μm in size. Experimental Setup Illumination: Linearly polarized 532 nm diode laser. Detection: Scattered light collected at 120° relative to the incident beam. Sensor: LUCID Vision Labs Triton™ TRI050S-QC polarization camera utilizing Polarsens Division-of-Focal-Plane (DoFP) technology Sample Medium: Purified water. File/Folder Name Description Units/Format 01_raw_intensity_images Contains demosaiced, full-resolution, green channel intensity images for the four polarization angles: 0°, 45°, 90°, and 135°. PNG 02_derived_images Contains the three calculated linear Stokes parameters and the two primary feature images: AOLP and DOLP PNG 03_ derived_images_masked AOLP and DOLP images with background pixels set to zero to isolate particles. PNG
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DoFP Polarimetric Microplastic Dataset: Raw and Derived Stokes/AOLP/DOLP Images
AI summary Read the abstract
Researchers developed a Division of Focal Plane (DoFP) polarimetric dataset containing raw and processed polarization images of three common microplastic polymer types — PP, HDPE, and LDPE — submerged in water. The dataset of 600 colorless, irregularly shaped particles (50-300 micrometers) was designed to support image-based classification of microplastics using Stokes, AOLP, and DOLP derived parameters.
DoFP Polarimetric Microplastic Dataset: Raw and Derived Stokes/AOLP/DOLP Images
AI summary Read the abstract
Researchers developed a Division of Focal Plane (DoFP) polarimetric dataset containing raw and processed polarization images of three common microplastic polymer types — PP, HDPE, and LDPE — submerged in water. The dataset of 600 colorless, irregularly shaped particles (50-300 micrometers) was designed to support image-based classification of microplastics using Stokes, AOLP, and DOLP derived parameters.
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Researchers explored digital holography and polarization imaging as a combined technique for characterizing and classifying microplastics in water, computing features including angle of polarization (AoP) and degree of linear polarization (DoLP) to distinguish microplastics from biological and natural particles. The method demonstrated potential for real-time, non-contact, in situ microplastic detection and water quality monitoring.
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