By April 27, 2022 Read More →

AI delivers ‘utopian’ vision of product presentation

220427_Scorpion_2Visitors to stand 4 at the UKIVA Machine Vision Conference on 28 April 2022 will see how Scorpion Vision’s stereo vision and neural network solution, the Scorpion 3D Neural Camera, can elevate the presentation of retail packaged fresh produce to unprecedented levels.

Demonstrations on harvested vegetables will show how Scorpion Vision is pushing the envelope in terms of what can be achieved by applying AI to machine vision in an automation context. By guaranteeing that processes such as sprout, carrot and leek trimming are consistently completed within the tightest visual tolerances, Scorpion’s bespoke AI approach enables food processors to achieve utopian presentation that will meet the approval of even the most discerning shoppers.

The Scorpion 3D Neural Camera has also been heralded as a food waste saviour, as food factories can put a stop to perfectly good food being discarded due to inconsistent and sub-standard inline preparation techniques.

The advent of AI presents an exciting opportunity to enhance the capabilities and performance of vision systems in food processing applications. On the back of this, many off-the-shelf AI-camera solutions have become available.

Paul Wilson, MD of Scorpion Vision, explains why these ‘plug and play’ cameras can’t match the consistent performance and premium presentation that can be achieved by Scorpion Vision’s 3D technology with bespoke AI: “Lots of companies have jumped onto the AI bandwagon, thinking that all you have to do is program a camera with deep learning software.

“It is not that simple, which is why, although off-the-shelf camera solutions appear cheaper at a glance, they rarely provide more than 80% reliability. Integrating AI into an automation system that works 100% of the time requires a deep understanding of the build challenges.”

Scorpion builds AI vision systems from scratch to deliver robust and reliable application-specific solutions to food processing problems.

Paul continues: “We already have our proven automation platform so have been able to build AI into that with great success. Our AI cameras are designed from the ground up to suit the application. That means we can optimise the design and the parameters to enhance performance on that product. If we want to use more powerful lighting or move the lighting outside the camera, for example, we can do, because we have complete control over the build.”

With an organic object such as a vegetable, there is no fixed size, shape or colour, and this presents a problem for classic machine vision camera systems that rely only on known shapes or patterns.

Accurate trimming is key to the presentation of vegetables destined for retail sale. If the leek is cut too short it ‘telescopes’ and dries out. If it is left too long, unsightly roots are left. However, a standard 3D camera will struggle to determine the stem plate when it is obscured by roots or soil. In this scenario, applying AI improves machine vision performance dramatically.

The system on show at the Machine Vision Conference is based on the 3D Stinger, designed to be used in cutting-edge 3D stereo vision applications. Scorpion Vision can also design automation systems incorporating machine vision technology from other manufacturers.

Since signing a distribution agreement for the UK and Ireland with fast-growing global camera and vision systems manufacturer Hikrobot in 2017, Scorpion Vision has installed a number of systems based on products from Hikrobot’s portfolio. Hikrobot has a dynamic R&D pipeline and at the Machine Vision Conference will present a number of new products including a 16K line scan camera.

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