Non-contact measurement & inspection
lighting conditions.” In addition, features such as a 24x digital zoom, auto white balance and automatic colour correction ensure precise capture of even the finest details. As a genuine industrial camera, it was designed with long-term component availability in mind – an important advantage over conventional consumer webcams.
Thanks to the 24x digital zoom, auto white balance and automatic colour correction, the camera captures every detail.
identification. Different architectures and scenarios are being tested. This allows different degrees of difficulty and realism to be simulated in order to test how robust the AI models are against folds, overlaps or rotations.
Initially, an object detection model analyses the images captured by the first camera mounted above the conveyor belt. It determines the type of garment, such as a T-shirt, trousers or a dress. The second camera scans the garments again from a height of approximately 5 centimetres, focusing on material properties and the detection of features such as stains or buttons. The identified image sections are cropped and passed on to a second AI model, which classifies the type of material – specifically distinguishing between woven and knitted fabrics. Finally, the analysis results are clearly displayed on a screen.
WHICH CAMERAS ARE USED?
For image capture, the Augsburg-based institute relies on uEye XC cameras from IDS, specifically the uEye XC Starter Set. The complete package includes a camera, tripod, cables and a macro lens, providing a ready-to-use solution for the research project. Key factors in the camera selection were its compact design, 13-megapixel sensor and ease of use, as Martin Kohnle, project manager for AI & Digitalisation at ITA, explains: “The uEye XC is as easy to use as a webcam, but has been specially developed for industrial applications. It delivers razor-sharp images even with varying object distances or challenging
“The Augsburg-based team relies on the free IDS peak camera software for image processing integration. The Software Development Kit (SDK) provides all necessary programming interfaces and tools for operating and controlling the cameras. “IDS peak enables straightforward and high- performance integration of our cameras via USB3 Vision. The uniform SDK structure greatly simplifies development, control and image acquisition. This enables us to implement our AI-based image processing workflows more quickly and adapt them flexibly,” Kohnle confirms.
WHAT IS NEXT?
The textile recycling market is increasingly moving towards data-driven, AI-based processes that require high-quality image data in real time. This increases the requirements for camera quality, synchronisation and API compatibility for the recycling studio. Research focuses in particular on the flexible integration of various sensor technologies into adaptive sorting and analysis systems. DETEX itself is also set to evolve: What is currently a conveyor-belt-based system will be expanded into a modular, mechanical-robotic overall solution that addresses both recycling and reuse. At its core will be a free-fall system enabling multi-perspective, 360° capture of textiles. In addition, a downstream, two-sided shot by robot-assisted grippers will allow for detailed analysis of further material characteristics. This approach makes it possible to capture a significantly broader range of information and to assign textiles even more precisely to suitable recycling or reuse pathways. Another important step towards a closed recycling loop – supported by industrial image processing.
IDS Imaging Development Systems
www.ids-imaging.com
ADVANCING FOOD SAFETY WITH AI
A
new report released by BCC Research indicates that AI technology applied to areas such as contaminant detection, traceability and compliance is projected to grow at a CAGR of 30.9 per cent by 2030. Anticipated to be valued at $13.7 billion, this will revolutionise food safety and strengthen quality control reports Phil Brown, sales director at Fortress Technology Europe. “Machine vision is integral to this key trend. Forming part of a larger inspection system, adding vision capabilities to existing technology, for example metal detection or X-ray, strengthens quality control by capturing an image and processing it against set quality control parameters.
“In inspection technology, vision is usually deployed for label verification, rather than food surface defects. For example, it can inspect the top and bottom of the pack to ensure that labels and promotional offer stickers are correctly placed and feature dates. The result is greater compliance with legislative food labelling rules.
“One of the most valuable ways to contribute to a safer, more secure and sustainable food supply chain, as well as maintain a competitive edge in the industry, is through process and operational optimisation. Leveraging smarter technology and predictive analytic tools can help to create a safer, digitised and more traceable food system. “There are various inspection configurations available to food processors, from standalone metal detectors, checkweighers, x-ray and vision systems, to combination systems in any arrangement of these technologies. One of the greatest benefits of combination units is that the data centre can be integrated, rather than trying to tie multiple disparate database formats together.
“Fortress is already using its proprietary data software package, Contact 4.0, across its metal detection and checkweighing technologies. It enables processors to review, collect data and securely oversee the performance of multiple Fortress metal detectors, checkweighers or combination inspection machines connected on the same network. “Deployment of this type of data reporting provides context to support rule-based machine learning. It also enhances human decision-making through the extraction and interpretation of data.“
Fortress Technology
fortresstechnology.co.uk
Instrumentation Monthly March 2026 23
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