LOGISTICS


operator intervention is required, if at all, and providing excellent read rates on barcodes and other symbols, Eyre highlighted a number of additional benefits of image-based technology of the type supplied by Cognex. To begin with, he explained that camera-based technology means that access to the image is available when a product fails a specific test. Image feedback also provides data about the process, which can be used to drive process improvements. He also pointed out that Cognex smart cameras are solid-state devices with no moving parts, and contain their own on-board processors, meaning no PCs are required. ‘Te future will see more pixels and more


processing power within our smart cameras, and the introduction of 3D and deep-learning platforms to address a myriad of applications that are currently labour intensive,’ he added.


‘Te implementation of Cognex’s image-


based Dataman products over traditional laser- based products allowed Edeka to increase read rates of incoming pallets by up to 8 per cent, reducing pallet re-work and thereby providing a major efficiency increase, while also ensuring all supplier labels are compliant with the GS1 standard,’ he said. ‘Zalando’s retrofit of older laser-based


technology with the latest image-based technology resulted in an increase in read rates of three per cent on their sorting system at their Erfurt, Germany, facility,’ Eyre added. In addition, Ocado, a major online grocery


company based in the UK, uses Cognex’s technology to maximise throughput at its warehouses in semi-automated processes. Beyond the simple identification of products,


Eyre said that Cognex is also using other image- based technologies, such as 2D and 3D machine vision, as well as deep learning technology, to carry out a number of distinct tasks, ranging from calculating the correct dimensions of products, checking for damage to boxes and cartons, and determining if boxes or totes are full to capacity, to assessing barcode quality, automating robotic picking and classifying products into categories for sorting. As well as enabling companies to automate processes and tasks to a level where less


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Slave to the algorithm Another vision technology commonly used in the logistics sector is optical character recognition (OCR), a process by which soſtware converts human-readable text into characters that can be stored, interpreted, and segmented by machines. One company focused on the development of such technology is Omron, which offers advanced optical character recognition functionality in its machine vision product line. ‘Allowing user control of customisable


parameters, [Omron’s] IntelliText OCR can be adjusted to recognise characters regardless of marking or printing method, including low contrast text on poor backgrounds,’ said Nico Hooiveld, EMEA market manager at Omron Europe. According to Hooiveld, the tool can also


read difficult characters on parts and products in automated identification, tracking and inspection applications – and is capable of reading text printed by various methods, including inkjet, drop on demand (DOD) and direct part marking. Moreover, he observed that an integrated multi-neural network allows the tool to train on character variations and store these in a font library for increased OCR speed as the library grows. An advanced character segmentation capability also allows the soſtware to parse characters, regardless of their uniformity or the precision of the print region, a function that Hooiveld pointed out is useful when print consistency, label placement, or text location is subject to variation. To aid segmentation in difficult reading environments, IntelliText OCR also offers image pre- processing, enabling the soſtware to run filters


on an image taken by a machine vision camera to produce what Hooiveld described as the cleanest image possible for OCR. ‘Unique to IntelliText OCR is the soſtware’s


image binarisation process, which converts the greyscale image taken by the camera to a binary image. Te binary image allows the user to see the image features that the soſtware is able to recognise as characters, and gives users the ability to set tolerances that determine how much of the image is in view. Tis allows the most difficult text to be adjusted for and read with ease,’ he said. In automated warehouse and logistics


applications, Hooiveld observed that 2D barcodes are predominantly used, largely thanks to their more reliable performance. In terms of logistics and supply chain applications more broadly, he also said that the Omron OCR technology has been used successfully at Del Monte, where the company implemented a vision inspection system to read OCR text and barcodes on canned fruits and vegetables – to ensure that the product code printed on the top of the can matched both the contents inside


The future will see more


pixels and more processing power … and the introduction of 3D and deep-learning platforms


the can and the label. Looking at automated warehousing in a broad sense, Hooiveld also singled out human-machine collaboration, aided by imaging and vision technology, as a major trend – Omron has recently launched its TM series of collaborative robots for manufacturing environments, where humans and machines work together. Te TM series will automate applications


such as picking, packing and screw-driving. Omron has also released a mobile-compatible model, which integrates into its LD series autonomous mobile robot. Tis means users can automate more complex tasks, such as pick- and-place onto a tray or container.


Self-driving vehicles Another company heavily engaged in the vision and automation sector is Vecna Robotics, which manufactures a fleet of self-driving vehicles, including tuggers, pallet jacks and robotic conveyors with payloads ranging from 20kg up to 4,500kg. A key feature of each


December 2018/January 2019 • Imaging and Machine Vision Europe 19


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