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Machine Vision: Food Quality & Grading

Sort & Detect

From specialty crops to seafood and poultry, the global food inspection industry needs
newer and more precise tools to meet stringent government regulations.

Uncertainty resulting from reliance on human inspectors or limited capability RGB cameras is creating a strong drive for adoption of advanced high-resolution imaging systems that are simultaneously robust, affordable, and easy to deploy.

Above: an example of a system with a Headwall MV.X built by reseller Visratek in Turkey. The perClass Mira runtime engine helps enable real-time spectral classification as shown by as products pass under the MV.X on a conveyor belt.

Improved ability to sort and timely detection of contamination by techniques like hyperspectral imaging help food producers assure the quality and consistency of their products and avoid costly and brand-damaging recalls.

The ability to grade food products based on numerous geometric and spectral classifications is a key differentiator for hyperspectral imaging sensors. Nuts and specialty crops can be inspected based not on simple ‘pass’ or ‘fail’ metrics, but on more subtle characteristics that maximize quality and throughput.

The image on the right displays orange ripeness based on non-contact hyperspectral imaging and analysis.

Hyperspectral_Oranges-Ripeness

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