Hyperspectral Imaging in Food Inspection Requires the Processing Speed of CoaXPress Frame Grabbers | Robotics

WOBURN, MA, APRIL 1, 2024 — Machine vision has spread rapidly in the inspection of agri-food commodities, including meat, fish, and particularly the automatic inspection of fruits and vegetables.

More accurate than human inspectors, machine vision systems can scan food for a variety of unique characteristics, such as its ripeness, size, shape, and color, as well as to detect the presence of blemishes, stems, seeds or dirt. Besides exerting influence on a product’s appearance, these characteristics measure its nutritional content and suitability for preservation.

While food inspection systems have long relied on RGB color sensors, there is a push to incorporate hyperspectral cameras operating in the ultraviolet, visible, and infrared spectral ranges. Hyperspectral cameras provide more detailed information, making them particularly well-suited for the classification of blended raw materials and the detection of contaminants. They can also quantify a product’s chemical composition, for instance, its levels of pH, sugar, fat, water, and salt content.

While hyperspectral imaging opens new opportunities, its addition to a machine vision system significantly increases the amount of data transmitted from the camera to the host PC. Overloading…

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