Developed originally for remote sensing applications involving imagery from aircraft and satellites, Hyperspectral Imaging (HSI) has become a commercially viable technique for industrial machine vision applications. HSI sensors act like thousands or millions of spectrometers providing chemical signatures from the reflected light at each pixel of an image. Headwall’s sensors cover wavelength ranges beyond the ability of the human eye to discern, from the ultraviolet and visible (UV-VIS) to the near-infrared (VNIR, NIR, and SWIR) wavelength ranges.
Hyperspectral imaging sensors can distinguish spectral features and detect potentially harmful foreign matter. They provide a means to sort and grade material such as food products, where value is often tied to characteristics that are often better and more consistently measured by an HSI system. The human eye is subject to fatigue or the effects of something as simple as varying amounts of coffee each day.
Inspecting specialty crops such as nuts and berries involves looking at vastly similar-looking items with small degrees of variability. With hyperspectral machine vision technology in place, even the slightest variation in color or tone can be distinguished.
Machine learning and artificial intelligence powered software such as perClass Mira® assist in building classification models and enable runtime processing. Model development is fast and intuitive, with perClass Mira controlling both Headwall’s MV-series systems and scanning systems, allowing a range of users with different levels of expertise in machine vision, quality monitoring, and process analytical applications both within and outside of production environments.
The latest generation sensors, such as the Headwall MV.C VNIR and MV.C NIR, are small and rugged for use in harsh environments such as those found in food inspection facilities. Reproducibility from one instrument to the next is a critical requirement where inspection accuracy across numerous lines must be maintained.