Zebra Technologies Corporation (NASDAQ: ZBRA), an innovator at the front line of business with solutions and partners that deliver a performance edge, today announced that it has unveiled Deep Learning Optical Character Recognition (DL-OCR). The solution supports manufacturers and warehousing operators who increasingly need fast, accurate, and reliable ready-to-use deep learning solutions for compliance, quality, and presence checks.
Zebra is unveiling the DL-OCR solution at VISION 2022 in Stuttgart, Germany—one of the largest and most important machine vision events in EMEA, from 4-6 Oct. 2022.
Getting an OCR inspection right can be challenging. A variety of factors including stylized fonts, blurred, distorted or obscured characters, reflective surfaces and complex, non-uniform backgrounds can make it impossible to achieve stable results using traditional OCR techniques.
The new industrial-quality DL-OCR tool is an add-on to Zebra Aurora™ software that makes reading text quick and easy. DL-OCR comes with a ready-to-use neural network that is pre-trained using thousands of different image samples. It can deliver high accuracy straight out of the box, even when dealing with very difficult cases. Users can create robust OCR applications in just a few simple steps—all without the need for machine vision expertise. The intuitive Zebra Aurora™ interface makes set-up easy.
“Our advanced OCR technology has been enhanced and optimized by machine vision experts to offer state-of-the-art, industrial reliability,” said Donato Montanari, Vice President and General Manager, Machine Vision, Zebra Technologies. “Users simply highlight the read area, and the software does the rest. Zebra Aurora™ works on most fonts out of the box—even stylized characters so there is no need to train fonts or maintain libraries.”
Zebra’s DL-OCR addresses the need for faster, more accurate forms of automation by warehousing operators and manufacturers. The tool is helping today’s industrial imaging professionals think and act more like data scientists.
“Our vision is to enable engineers to harness the latest innovations in the field by making them more accessible to implement and leverage. It means engineers can think and act more like data scientists in the face of increasing volumes and varieties of data, and better understand the workings and business benefits of deep learning solutions,” said Montanari. “Being able to sense, analyze and act in real-time can be achieved with ready-to-use deep learning tools that capture and analyze data at the edge.”
During VISION 2022, Zebra’s Machine Vision Product Manager, Jim Witherspoon will deliver a workshop on Thursday, 6 Oct. 10.40-11.00 in Hall 8, Stand C70 discussing the topic of ‘From Barcode Reading to Vision to Deep Learning’.
Delegates and members of the media are invited to meet Zebra’s machine vision executives in Hall 8 booth 8B30, to discuss more ways that Zebra is meeting the machine vision needs of customers following its acquisitions of Aurora Vision in 2021 and Matrox Imaging in 2022. Delegates can also explore innovative live demonstrations of Zebra’s expansive hardware and software portfolio, including Zebra Aurora™ Studio, Library, and Deep Learning options.
At booth 8C45, Matrox Imaging will introduce the Matrox GevIQ – the industry’s first 10+ GbE smart network interface card (NIC) specifically for GigE Vision® acquisition – along with Matrox Design Assistant™ X 22H2 software and the Matrox 4Sight EV7 industrial computer.
KEY TAKEAWAYS
• Zebra is unveiling its new Deep Learning Optical Character Recognition (DL-OCR) tool as a Zebra Aurora add-on for warehousing operators and manufacturers who need a powerful, out-of-the-box deep learning solution.
• The DL-OCR tool comes with a ready-to-use neural network that can deliver high accuracy straight out-of-the-box, even when dealing with very difficult cases.
• The tool will be available to Zebra industrial automation partners in the near future.
• Zebra is also hosting a workshop ‘From Barcode Reading to Vision to Deep Learning’ to support and encourage industrial imaging professionals to think and act more like data scientists.
