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Zebra Aurora™ Deep
Learning OCR Tool
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Reliable, Accurate Reads
Without Training
Zebra Aurora Interface - Deep Learning OCR job setup
Zebra Aurora software is a unified platform that gives end users of all skill sets control over all Zebra
fixed industrial scanners and machine vision smart cameras, simplifying management of enterprise-wide
manufacturing and logistics automation solutions. Among the software’s many capabilities is optical
character recognition (OCR), which automatically extracts information from images.

Oftentimes, training and retraining consumes a significant amount of time during OCR setup. Companies
today need machine vision products that can dynamically adjust to such scenarios and deliver a reliable
read. Traditional OCR applications may fall short when working with tough to read or low contrast characters
on confusing backgrounds. With the new Deep Learning OCR tool, font training becomes redundant, as it
delivers reliable, accurate reads without having to train numerous different texts or fonts. The tool leverages
state-of-the-art techniques that allow novices to quickly and easily set up highly accurate text recognition and
character reading applications.
Zebra Aurora™ Deep Learning OCR Tool
Approachability for End Users
End users unfamiliar with OCR technology or general machine vision may encounter challenges in system
setup. Challenges that can impact success include how a code is printed, the type of surface its applied
on, the way the code is illuminated, and the way its captured by the camera. The Deep Learning OCR tool
removes these roadblocks. The approachable, easy-to-deploy machine vision system requires no coding or
programming expertise. This allows companies to quickly install new deep learning-based OCR applications
that could previously not be automated.
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Zebra Aurora™ Deep Learning OCR Tool
Swift Setup for Systems Integrators
For systems integrators, Zebra Aurora’s Deep Learning OCR tool saves significant setup and deployment
time. The software requires no font training. Most non-deep learning OCR technologies require samples of
all potential OCR fonts — and all possible variations of a given font — and subsequent time spent training the
software on them. Integrators might spend months setting up an OCR font because the system has not yet
encountered a particular variant of letter, such as one that is rotated or skewed or stretched or compressed
due to variations in line speed. Instead, the integrator can setup the scanner or camera and turn the intuitive
interface over to a control engineer or another plant floor operator to begin using the deep learning–powered
OCR tool.
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As Simple as Drawing a Box
Zero Training for Faster Deployment
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Zebra’s DLB OCR Tool can handle a great amount of process variation. The robust and powerful algorithms ensure maximum readability
and throughput.
Manufacturing and logistics environments need machine vision systems that offer flexibility and ease of use. Requirements can quickly change, or new parts can be introduced. Streamlining the process of adjusting an automation system helps make flexibility and ease of use possible. Zebra Aurora’s Deep Learning OCR offers a pretrained model that allows users to deploy the tool directly on a camera, removing the time-intensive training portion of deep learning development entirely, including the training of new fonts or texts.
East of Use
Manufacturing and logistics environments need machine vision systems that offer flexibility and ease of use. Requirements can quickly change, or new parts can be introduced. Streamlining the process of adjusting an automation system helps make flexibility and ease of use possible. Zebra Aurora’s Deep Learning OCR offers a pretrained model that allows users to deploy the tool directly on a camera, removing the time-intensive training portion of deep learning development entirely, including the training of new fonts or texts.
Confident Code Reading
With the Deep Learning OCR tool, end users can set minimum confidence scores to ensure a reliable read. In addition, users can look at the overall confidence of a given string and then drill down to the character-to character quality to ensure the algorithm is reading correctly and that the highest-confidence reads are being delivered and then make adjustments as needed.
Choose From a Range Machine Vision Toolsets
With the new OCR tool, end users can draw a box around an area of interest for fixturing, which also teaches the algorithm the fonts, and capture textual information from the image. End users also can set thresholds that will help differentiate between different character strings, such as mathematical, alphanumeric size, or spacing. In addition, decoder performance packages can be added to any FS fixed industrial scanner or VS smart camera once. End users also have a range of machine vision tool sets available to choose from.
Machine Vision Tool Sets (Decoder Package Included in Standard Tool Sets)
Tool
Object Locate
Description
Find high-contrast features
Sensor
Standard
Pixel Counter
Count the number of pixels in a designated range
Brightness
Return the average brightness of an area
Contrast
Return the average contrast of an area
Edge Tool
Find edges for fixturing and presence/absence
Distance Tool
Measure the distance between two tools previously created
Advanced Pattern
Find challenging features with variant lights, scaling, occlusions, etc.
Blob
Find, sort, and count areas with similar pixels
1D/2D/DPM
Read 1D, 2D, and DPM barcodes
Find Circle
Find and measure circles
Caliper Tool
Measure the distance by finding two edges
Filters
Enhance image quality for robust inspections
OCV/Flaw
Find residual or missing pixels from a trained shape
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Contact Power-Flo Technologies to learn more.
Power-Flo Technologies is a unique organization of distributors, fabricators, manufacturers, and service firms that bring innovative solutions to businesses throughout the New York metropolitan and New England areas. As a certified Zebra partner, we offer the expertise and knowledge needed to help you get the most out of the latest Fixed Industrial Scanners and Machine Vision Systems.
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