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Embedded special


harvesting B


High-tech


Te harvesting process could be on the verge of a complete overhaul thanks to machine vision, Matthew Dale finds


roccoli is a difficult crop to harvest. Firstly, the window for when broccoli heads reach the correct size for picking is only three


days. If the crop is harvested too early the heads will be under developed; too late and they’ll be too large. In addition, the weight of a broccoli head that a supermarket asks for can vary from one supermarket to another, complicating the harvesting process further. Manual harvesting currently results in up to


30 per cent of crops being leſt in the field because of the speeds at which the pickers are required to work. But now a combination of machine vision, deep learning – whereby the algorithm is trained to recognise variation using lots of data – and robotics has the potential to automate and replace these manual harvesting methods. One such robotic system, being built by


integrator Capture Automation in partnership with Stemmer Imaging, is designed to harvest broccoli. ‘Ideally, vision can be used to harvest at source,’ Ky Ellen, machine vision consultant at Capture Automation, commented. ‘Te system is set up to collect a certain amount of broccoli heads of a particular size and is then sent on its way to harvest them automatically.’ Stemmer Imaging and Capture Automation


are currently involved in a long-term partnership that designs and delivers vision systems for these automated harvesting machines, which enables picking to take place outside normal working hours, according to Chris Pitt, sales manager at Stemmer Imaging. ‘Picking at night time is also more beneficial, as the product stays cooler and fresher for longer,’ he said. One of the problems with manual harvesting is that growers have no knowledge of what remains in


Vision technology can be used to discern weeds from crops, such as this pigweed growing alongside cotton plants


the field aſter some of the crop has been harvested. ‘With an imaging system, it’s not only possible to collect data on the crops being picked, but also the data of the plants leſt in the ground,’ said Ellen. ‘You can send back information on why crops have been leſt in the field, perhaps because they’re a certain size. Tis allows you to come back at a later date and harvest the rest of the field.’ Vision systems enable farmers to harvest all their


crops at the optimal time. ‘Vision technology could be used to start grazing a field as soon as growers believe their crops are close to being ready,’ Ellen explained. ‘Te system would go and only pick the crops that are ready for a particular order, while also sending data back on the crops that are leſt in the field. Tis is quite valuable, as the data can then be correlated with the weather forecast to estimate when the rest of the crops will be ready, so then the machine can be sent out again to pick everything at the right time.’ Te new automated harvesting systems are


currently still in the trial phase and are being guided using 3D vision, which offers numerous advantages over more traditional 2D imaging, according to Pitt,


32 Imaging and Machine Vision Europe • June/July 2017


such as being able to discern between weeds and crops. ‘Te main reason that 3D imaging is better for


this, is that with 2D imaging everything within the image is based on the intensity of light that’s being reflected back from the product, rather than the product’s physical shape,’ commented Ellen. ‘Terefore, with 2D imaging, the closer the product is to the camera, the brighter the image; if it’s further away, then you’ll get a darker image. Tis adds a lot of variability. ‘Part of the challenge with broccoli is separating


the leaf from the head, so if one of the leaves from one plant is covering the head of another, a 2D system will struggle to tell the two apart,’ Ellen continued. ‘With a 3D system, it can be trained to look for a domed shape and a different texture to a leaf, making them easier to separate.’ Te 3D vision system provided by Stemmer


Imaging for this application is LMI’s Gocator camera, an all-in-one calibrated solution with an IP67 rating, meaning it is both dust and waterproof, and therefore suitable for the harsh conditions experienced out in a field. A laser is used alongside


@imveurope


www.imveurope.com


Blue River Technology


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