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Food Business Review | Wednesday, February 16, 2022

Machine Vision has set foot in the food industry for quite a long time. Still, its latest developments support a broad array of exciting industrial technologies.
FREMONT, CA: With machines becoming more intelligent every day, the food industry is experiencing abundant modern applications and numerous ways to benefit from them. Machine learning and machine vision are expressly valuable additions to the supply chain for the industry.
Machine vision’s application in the food industry
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Machine vision can be applied significantly to a food processing environment, with the latest modification in the technology cropping up frequently. The following is a synopsis of the ways different types of machine vision systems serve distinct functions in the food and beverage field.
1. Automated Sorting for Big Product Batches
It is effortless for machine vision inspection systems to become part of an immense automation effort. Automation is of great advantage to the food and beverage sector to improve worker safety and proficiency. Moreover, it also offers better quality control across the organisation.
Inspection stations have machine vision cameras that scan every product or whole batches of products to detect flaws. However, physically segregating these items might be as efficient as seeing them. Due to this reason, machine vision is an appropriate companion to compressed air systems and others, which can blow away and eradicate every single grain of rice from a bigger batch in preparation.
2. 3-D Machine and Frame Grabbing
Machine vision systems want optimum lighting for performing successful inspections. Unnecessary products can slip through easily onto shelves and into clients’ homes if the part of scanning is in shadow.
When conducting visual inspections, sometimes food products have explicit requirements. For example, it is challenging or sometimes not possible for the human eyes to perform detailed scanning of thousands of nuts or peas as they pass through a conveyor belt. The 3-D machine offers a tool known as ‘frame grabbing,’ which takes stills of tens of thousands of small, moving items at once to find errors and perform sorting.
3. Near-Infrared Cameras
Machine vision comes in many forms, including barcode and QR code readers. In addition, the latest NIR(near-infrared) cameras considerably enhance machine vision capabilities and usefulness.
In several cases, physical damage to vegetables and fruits does not instantly surface on the outside. NIR technology does the task of expanding the light spectrum cameras can observe, thus allowing them to recognise interior damage before it appears on the exterior.
It is essential to understand that neither machine vision nor machine learning is about developing hardware that thinks and observes as humans do. However, with the appropriate approach, these systems can outperform human employees.
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