Food and Beverage

Automated Meat and Poultry Inspection

Automatically grade meat and poultry to ensure correct pricing

Defect detected on chicken breast in a container

関連製品

VisionPro ViDi Product Tile

VisionPro Deep Learning

ディープラーニング採用の工業用画像解析向けグラフィカルプログラミング環境

In-Sight D900

In-Sight D900

ディープラーニング採用 In-Sight ViDi 画像処理ソフトウェア搭載

Organic meats and poultry are premium products sold to discriminating customers, but they are still packaged in large volumes with automation machinery. The label on the cut of meat or poultry part must be accurate. Accurate classification also ensures that the appropriate price is charged for each cut. Industrial packaging still suffers from the possible inclusion of physical contaminants.

Organic meat and poultry vary more in size, color, and other aspects than factory-raised products because of the range of ways in which they are raised and slaughtered. These variations in appearance make it difficult for conventional machine vision to accurately solve visual meat classification applications, particularly when they have already been packaged with a wrap containing a visually confusing logo with printing on it.

X-ray scanning can find metal contaminants, but plastic or polystyrene foam must be identified visually. Given their random appearance and location, conventional machine vision often misses such contamination.

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Cognex Deep Learning is an effective solution for meat quality inspection. It trains on labeled sets of images of each meat cut or poultry part. The classification tool will then accept the range of natural variation while accurately classifying each piece, ensuring that no part is graded lower than it should be, so the product can be sold at the highest fair price.

The defect detection tool quickly spots any bits of physical contamination, whether from damaged packaging, machinery, or other sources and flags them before the product moves on to shipping. This ensures that all cuts shipped are classified and priced correctly, improving both customer satisfaction and revenues.

 

Classification results on different cuts of poultry

 

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