ADVERTISEMENT FEATURE Machine vision


HOW SPECTRAL OPTICS ARE IMPROVING AUTOMATED INSPECTION AND SORTING


For NIR and SWIR imaging applications, spectral filtering is particularly important because accurate material classification often relies on detecting relatively small differences in reflected wavelengths.


Machine vision is now a standard part of manufacturing, helping production lines inspect products, identify defects, and verify quality at speed. Increasingly, however, manufacturers need information that cannot be captured by visible-light cameras alone, says Knight Optical


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aterials, coatings, contaminants, and product variations often appear identical under conventional


imaging systems. To address this challenge, many automated inspection and sorting systems are adopting spectral imaging technologies that analyse information beyond the visible spectrum. The quality of the data produced by these systems depends not only on the camera and software, but also on the optical components that control how light reaches the detector. Looking beyond conventional machine vision Standard machine vision systems are designed to capture images in the visible wavelength range. For many inspection tasks, this remains effective. Surface defects, dimensional measurements, colour variations, and assembly checks can all be performed using conventional imaging systems.


Some applications require more detailed information. Different materials absorb and reflect light differently across the electromagnetic spectrum, creating distinct spectral signatures that can be used for identification and classification. This has led to growing use of near


infrared (NIR), short-wave infrared (SWIR), and hyperspectral imaging technologies throughout industrial automation. Spectral imaging in automated sorting Recycling is one area where spectral imaging has become particularly valuable.


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Mixed plastics often appear visually similar, making them difficult to separate using conventional cameras. Hyperspectral imaging systems can analyse reflected light across multiple wavelengths, allowing materials such as PET, HDPE, PVC, polypropylene, and polystyrene to be identified according to their spectral characteristics. These measurements must often be performed while materials move rapidly through the sorting process. At these speeds, the quality of the optical system becomes critical. Insufficient light transmission, unwanted reflections, or inconsistent spectral data can reduce classification accuracy and affect throughput.


The same principles apply in other automated inspection environments where precise material identification is required. Managing unwanted light Industrial environments rarely provide ideal imaging conditions. Changes in ambient lighting, reflections from machinery, and varying surface finishes can introduce optical noise that affects measurement quality. To improve consistency, many systems use


interference bandpass filters to isolate specific wavelength ranges while blocking unwanted light. By allowing only the wavelengths relevant to the inspection task to reach the detector, these filters improve contrast and reduce measurement variability.


Filter selection depends on the operating


environment and application requirements. Broadband filters are often used where maximum light throughput is required, while narrower bandwidth filters can help suppress background interference and improve measurement stability.


Reliability in industrial environments Automated inspection systems are frequently exposed to dust, vibration, temperature fluctuations, and routine cleaning procedures. Any deterioration in optical performance can affect measurement accuracy over time. Protective optical windows are commonly used to shield internal components from contamination and physical damage. Sapphire windows are often selected where high durability and excellent optical transmission are required.


Optical coatings can also improve long- term performance. Dielectric coatings help maintain transmission characteristics under varying environmental conditions, while diamond-like carbon (DLC) coatings provide additional resistance to abrasion in demanding applications.


Maintaining stable optical performance is particularly important in automated systems that operate continuously, where small changes can gradually influence inspection results. Optics as a performance factor As automated inspection systems become more sophisticated, the quality of the optical data entering the system becomes increasingly important.


Spectral imaging technologies enable manufacturers to move beyond simple pass/ fail inspection and gain deeper insight into material composition, contamination, and product quality. Achieving reliable results depends on capturing clean, repeatable optical data under real operating conditions. From machine vision inspection to high- speed sorting and material identification, optics remain a fundamental component of system performance.


Knight Optical supplies precision optical components for machine vision and industrial imaging applications.


Knight Optical www.knightoptical.com


Automation | October 2026 31


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