Advanced Imaging And Deep Learning Technologies Execute Critical Packaging Inspection
While machine vision applications have been highly successful for decades using "analytical" vision tools, deep learning is able to successfully solve very complex classification and object detection problems with ease.
Product packaging - in an extremely broad range of markets from food to pharma - frequently incorporates an extremely important sealing technology called “tamper evident” seals. The purpose of these mechanisms is to help ensure the safety, quality, and often the shelf life of the product. Driven by a tragic incident of malicious product contamination in the early 1980s, the FDA since has mandated tamper evident packaging for all pharmaceutical OTC products and manufacturers of most all consumable products in other markets follow that lead. Several standard sealing techniques are used, and in each case verification of the integrity of the seals during packaging is a step that is critical to the process.
For a wide range of applications in packaging with plastic bottles, the use of a foil seal under the cap is one of the standard, common “tamper-evident-packaging” (TEP) implementations. In this article, we will discuss the integration of advanced imaging techniques with deep learning analysis used to successfully inspect foil seal integrity with high reliability.