Scorpion Vision, a machine vision automation producer, has created a 3D stereo vision-based inspection solution that ensures “perfect presentation” for chocolate gifting trays.
By achieving near 100% accuracy in a task typically performed by one or two humans, Scorpion’s solution addresses the challenges of unskilled labour shortages for confectionery manufacturers and packers while increasing line efficiency.
The system uses Scorpion 3D Venom cameras to inspect chocolates that have been placed in compartmentalised trays by robots performing pick-and-place operations. After being placed, chocolates will occasionally bounce up and either turn upside down or leap out of the tray.
Scorpion has engineered an advanced vision solution that captures 3D images of the chocolates and takes precision shape measurements. This enables the system to confirm the correct placement and position of each chocolate within its designated compartment.
Scorpion says that at the core of the solution is the global shutter Scorpion 3D Venom camera. The camera is said to be “ideal for applications in cutting-edge 3D stereo vision systems owing to its short baseline”.
Paul Wilson, managing director at Scorpion Vision, explained: “The shorter the baseline, the more accurate the stereo or ‘z’ depth – a camera trait that is essential for reliable decision-making in this application”.
He continued: “The system requires several data sets to determine, with high accuracy, whether the right chocolate is in the right position. As well as generating a 3D profile, it relies on precise dimensional measurements, 2D imaging and colour imaging to build a complete and detailed picture. With this data combination, it can even analyse the texture of each chocolate to determine whether they are correctly placed. If a chocolate is upside down, for example, the vision system recognises that the texture or pattern on that chocolate is different to the reference.”
Although the solution was originally developed with chocolate manufacturing in mind, Scorpion states that it “could just as easily be applied on any production line where compartmentalised presentation trays are used – from cupcakes, patisserie items and pastries to biscuit selections”. In addition, it is possible to overlay this solution with artificial intelligence (AI) for enhanced performance and reliability.
Wilson added: “We create a profile of the product in 3D and analyse it for certain reference features. We then use AI to enhance extraction of these features – essentially training the vision system to identify and locate anomalies. The application of AI makes texture and pattern verification easier to do and even more reliable than with the use of 3D vision alone.”
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