X-RAY INSPECTION


Spectral X-ray camera offers first for finding plastic in food


Deep Detection’s Colin Burnham says advances in X-ray detection promise much for industrial inspection. Greg Blackman reports


A


n industrial X-ray camera able to perform spectral imaging – which


hasn’t been possible before – is about to be launched into the marketplace. Deep Detection was founded


in July 2020 as a spin-out from the Institute de Fisica d’Altes Energie in Barcelona. It has recently secured €1 million in a funding round led by photonics investor Vigo Ventures for its X-ray camera called PhotonAI. Te company is currently


involved in proof-of-concept trials with future clients and food production firms to address inspection challenges, the main one being detecting plastic contamination in food. ‘Tere are no detection


methods today that can pick up on plastics [in food production],’ commented Colin Burnham, COO of Deep Detection and ex- senior director at PepsiCo. Plastics are used across the


entire supply chain for food manufacturing, whether that’s plastic containers that move bulk material around from farms to factories, or the drives inside conveyor belts, the seals inside pipes and tube work, or from packaging and handheld tools. Burnham said that there are


around 130 product recalls every year in Europe because of a serious risk of foreign bodies in food, and around 30 per cent of those are plastics. ‘Recalls in the food industry are highly disruptive,’ Burnham


added. Tere’s a lot of cost associated with recalls, because it involves product storage, product disposal, liabilities, and not having a product in the market means lost sales. Deep Detection’s camera


is able to detect plastic contamination in food where other inspection techniques cannot. Te science behind the


technology comes from particle physics; it is based on photon counting using microelectronics with a very low noise base. Traditional X-ray machines


use a scintillator to detect X-rays and turn them into light, which is then picked up by photodiodes. Te indirect detection method means information is lost. Deep Detection’s sensor is able to detect X-rays directly using photon counting and then digitally bin the energy data. Tis means it can do spectral imaging, which is ‘completely new in X-ray’, Burnham said. ‘You can use that spectral data


to separate out images,’ Burnham explained. Deep Detection will initially offer a camera with two levels of spectra, and is working to produce a multi-level spectral camera. X-rays attenuate at a different


rate according to their energy level, so the camera captures a spectral fingerprint in discrete energy bands. A common application would


be to measure the percentage of fat in meat products, for


4 IMAGING AND MACHINE VISION EUROPE DECEMBER 2021/JANUARY 2022


example, to grade meat and send it to different upstream clients. At the same time, the PhotonAI camera can inspect for foreign bodies. Te importance of spectral


information when looking for lightweight materials like plastics is the ability to separate out images. Te camera is able to read the energy signatures in X-ray at lower energy levels than conventional scintillators. Plastics absorb in a low-energy band, so being able to separate out images into different energy bands while having a low noise floor means the camera can differentiate and detect those materials. Te challenge with spectral


imaging in X-ray is that the energy is so high – the wavelength so short – that it’s difficult to separate out different X-ray wavelength bands, as


‘We’re taking [photon counting] and building it into an industrial detector for line scanning’


happens for RGB in the visible spectrum, explained Burnham. To be able to do that involves measuring photon by photon and grouping that data into different bands. Medical equipment like CT


scanners is adopting this photon counting technology, and achieving ‘phenomenal gains’, said Burnham. Te spectral data is used to separate out not just flesh from bone, but tissue down to the level of blood vessels.


‘Tey’re getting very precise results,’ he said. ‘We’re taking that same


science, building it into an industrial detector for line scanning, making it accessible at a price and performance level, while still getting the high- quality data,’ Burnham said. ‘We believe we can take


those learnings [in medicine] and implement them for these industrial solutions,’ he added. Burnham said the camera


is more expensive than a conventional camera, but the extra value brings a significant benefit. Te camera is compatible with existing X-ray systems and machines, so integration is straightforward. Te camera uses a 330µm


pixel, so achieves similar spatial resolution to a conventional detector, which has around a 400µm pixel. However, it’s a precise pixel-by-pixel measurement, which allows multi-energy images to stay registered to each other. Burnham said the camera


is able to read enough data to produce a high enough contrast-to-noise ratio to detect foreign objects in food moving at 60m/min, which is what food production lines typically run at. In addition, because the data is grouped digitally, the detector can be configured for the energy band of most interest, or trade off spatial resolution with spectral resolution or speed – it can adapt to the needs of different inspection tasks. Deep Detection plans to offer


industrial prototypes for clients to test early next year. It will then launch the full series in the fourth quarter of 2022 or early in 2023. O


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Deep Detection


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