XyloTron

XyloTron enables macroscopic field identification of wood and charcoal products to support verification and monitoring of forest-derived materials.

Key Features:

• Multi-Illumination Imaging System: Uses visible and ultraviolet (UV) light sources to capture macroscopic images of wood products under varied lighting conditions.
• Deep Learning Models for Identification: Employs advanced deep learning models to perform automatic classification of wood and charcoal products.
• Software Integration for Camera Control: Provides software components for camera control and image capture during field imaging.

Scientific Applications:

• Automatic Wood Identification: Uses visible light imaging and automated classification to identify wood species for verification of sourcing and trade compliance.
• Charcoal Identification: Applies imaging and classification methods to identify charcoal products for monitoring production and supply chains.
• Human-Mediated Wood Identification: Utilizes UV illumination to enhance visualization of macroscopic wood features for human-assisted identification.
• Field Imaging and Metrology: Supports macroscopic imaging and material characterization of substrates for field metrology and related analyses.

Methodology:

Image acquisition under visible and ultraviolet illumination controlled by camera-control software, followed by automated classification using deep learning models.