Harness the power of hyperspectral cameras to revolutionize textile recycling and improve sustainability. Using the advanced MV.C NIR sensor by Headwall and perClass Mira software, you can elevate your sorting processes, tackling one of the most pressing challenges in waste management—efficient textile classification.
Textile recycling remains a significant global issue, with only 15% of post-consumer textile waste recycled while 85% ends up in landfills, according to the US EPA. Traditional sorting methods, like air classifiers, struggle with fabrics of similar density and texture, while chemical sorting methods, although precise, require destructive processes and are limited to specific materials like polyester.
RGB and multispectral imaging, while providing some insights, fall short in distinguishing between fabrics with subtle differences. The ideal solution is a contactless sorting system that can classify diverse fabrics and blends at high speed. Headwall's hyperspectral imaging technology (HSI), combined with perClass Mira's machine learning software, addresses this challenge with unmatched precision and efficiency.
Hyperspectral cameras analyze the entire light spectrum reflected by materials, providing unparalleled accuracy in identifying textile compositions. This allows recyclers to distinguish even minor differences between fabrics, making it an essential tool for sustainable textile recycling.
In a recent trial, fabric samples with varying compositions—cotton, wool, and synthetic blends—were scanned using the MV.C NIR sensor and analyzed with perClass Mira software. A spectral library of pure fabrics such as acrylic, cotton, linen, nylon, polyester, viscose, and wool was created, enabling the development of precise classification and regression models.
Many textiles share similar physical and chemical properties, making traditional sorters ineffective. Using AI-driven hyperspectral imaging and machine learning, Headwall’s system builds accurate binary models to classify fabrics, distinguishing between specific materials like polyester and non-polyester with remarkable precision.
Most garments are made from fabric blends, requiring advanced methods to estimate their composition. Headwall's hyperspectral cameras and perClass Mira's software analyze spectral features in the near-infrared (NIR) range (900–1700 nm), identifying both pure fabrics and blended materials. This enables recyclers to separate textiles more effectively, ensuring higher-quality recycled outputs.
Headwall's MV.C NIR system, paired with perClass Mira’s software, offers a sustainable solution for textile classification and recycling. With real-time, contactless sensing capabilities, this technology makes sorting faster, more accurate, and environmentally friendly.
Want to Learn More?The MV.C NIR by Headwall, combined with Mira stage software, allows you to elevate your textile sorting processes to a whole new level.
