Projects AI Based Post Harvest Vegetable Processing

Traditional optical sorting and grading systems use classic machine vision to look for features in the product image. These are known or expected features, such as the tip of a carrot or the flat bit of the stem on a leek when it transitions to the roots. Most of the time these features conform to a pattern or shape that is expected. With an organic object such as a vegetable, there is never a fixed size, shape or colour of anything, and this presents a problem to classic camera systems that only rely on known shapes or patterns because the variation means that there will always be a high percentage of unknowns.

In an automation system that relies on classic machine vision, this can translate to a relatively poor yield output from the machine.

For more information download our case study

60%
of leeks may be correctly processed with the roots cut correctly at the exact point.

20%
of leeks may be cut roughly, at a poor angle or slightly too short/too long.

20%
of leeks may be written off or not cut at all.

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