Non-contact measurement & inspection
AI AND IMAGE PROCESSING IMPROVE TEXTILE RECYCLING EFFICIENCY
T
he mountain of old textiles continues to grow in Germany every year. Less than one per cent of this enters a closed recycling loop. Reasons for this include so-called “fast fashion”, which leads to an increasing amount of low-quality textiles, as well as the wide variety of materials, which makes efficient recycling even more difficult. Today, sorting is mostly done manually and is almost impossible to manage given the quantities involved: Of around 1.4 million tonnes, only about 200,000 tonnes are actually checked and allocated. The rest is thermally recycled or exported abroad. Automated processes are therefore a key lever for keeping significantly more used textiles in circulation.
The Recycling Atelier at the Augsburg Institute for Textile Technology (ITA) is tackling this challenge. As a model factory, it maps the entire process of mechanical textile recycling. The focus
is on a holistic concept that does not optimise individual sub-processes but rather takes the entire system into account. This approach led to the development of DETEX – an AI-based system for the automatic sorting of textiles. With the help of artificial intelligence and two high-resolution uEye XC cameras from IDS Imaging Development Systems, DETEX captures the essential features of the garments and assigns them precisely to specific categories. This makes sorting more accurate and lays the foundation for efficient recycling.
WHY IS SORTING OLD CLOTHES SO IMPORTANT?
Before worn-out trousers, T-shirts or jumpers can be turned into something new, they must first be mechanically processed. The aim of this process is to create entirely new fabrics from the used garments. To achieve this, they are shredded, freed from buttons or zippers, and broken down into individual fibres. Preserving fibre length during this process is crucial to the quality of the recycled material produced. Differences in fabric structure and areal density must also be taken into account during processing. Precise classification into material categories is therefore essential and determines the subsequent handling of the textiles.
Until now, sorting has been done mainly by hand – a time-consuming process that requires a high level of expertise. In other industries, such tasks have long been performed by automated, AI-supported recognition systems. This is precisely where DETEX comes in: The research project is developing and testing AI models designed to make the sorting of used textiles significantly more efficient.
HOW DOES THE SYSTEM WORK? DETEX relies on intelligent image processing to automatically recognise and classify textiles. Two
The AI uses a uEye XC camera to determine the type of material used in the textiles.
The analysis results are shown on a display.
high-resolution industrial cameras provide the necessary images by scanning garments as they move along a conveyor belt. Neural networks analyse the images and recognise patterns and structures based on previously learned data. To enable this, they were trained in advance using a large number of sample images, including photographs of various garments as well as close-up images of different fabric types. At least 3,000 samples per clothing category were required. This training data had to be manually categorized beforehand, for example by labelling an image of trousers as “trousers“. On this basis, DETEX can quickly and reliably assign new images to the appropriate textile categories. For precise analysis, DETEX works with pre-trained neural networks – one model each for classification, object recognition and material
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March 2026 Instrumentation Monthly
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