Deploying Ocr Systems in Industrial Manufacturing.whitepaperpdf.render

8/10/2019 Deploying Ocr Systems in Industrial Manufacturing.whitepaperpdf.render

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2 Machine visionsystem makes light ofhigh-speed printing

inspection

10 Modular vision systemeases printed circuitboard traceability

15 Machine VisionAdds Traceability toPackaging

EDITORIAL DIGEST

Deploying OCRin industrialmanufacturingTodays manufacturing environments

demand that packaged products can be

seamlessly tracked from manufacturing to

their final destination. To do so, companies

in the food, packaging and printing

industries require rugged optical character

recognition (OCR) systems that can be easily

deployed to track and trace their products

as they are manufactured and packaged on

assembly lines. This series of articles show

how such manufacturers have designed

and deployed automated quality control and

inspection systems using OCR to monitor

products as disposable plastic moldings,printing materials and cases of packaged

fruit as they are produced.

VisionSystemsD E S I G N

VisionSystems

Reprinted with revisions to format from Vision Systems Design. Copyright 2014 by PennWell Corp


2/19Vision Systems Design:: EDITORIAL DIGEST

2

Originally published May 2014

Machine vision system

makes light of high-speedprinting inspection

A vision-based inspection system ensures the

quality and data integrity of printed materials.

by LARRY WILLOUGHBY

ORGANIZATIONS IN FINANCE, insurance, healthcare, government

and utilities are all tasked with delivering printed communications

to their customers accurately and on-

schedule. These document services

organizations - whether they be a corporate in-plant

team or a print-for-pay service bureau - produce,

print and mail personal credit card statements,

explanation of benefits (EOBs), negotiable documents

and investment summaries.

With the introduction of high-speed inkjet technology,

color now provides an exciting new dimension to

printed materials. Promotional offerings can be

added to these transactional documents delivering

personalized campaigns to individual customers.This is a powerful marketing strategy because

transactional documents are typically opened and

read as they contain customer-critical information.

With the speeds of these new digital color inkjet

printers it is difficult to monitor the overall quality of

the output. To add to the challenge, new supporting

Figure 1: The DocuVision 8600 Color

Print Verification System (PVS) is an

in-line, full-page print quality and data

integrity inspection system built for

interoperability with high-speed color

inkjet printers that can inspect images

at web speeds up to 650 ft/min.
http://www.vision-systems.com/http://www.vision-systems.com/


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Machine vision system makes light of high-speed printing inspection

Vision Systems Design:: EDITORIAL DIGEST

paper handling equipment is often used. Previously, paper would be fed into a

printer, printed and stacked into folds where it could be manually inspected by

an operator. Now the printed paper is rewound onto a paper handling device

at speeds up to 1000 ft per minute and beyond, further limiting visual manual

inspection.

Hence, these organizations are now faced with the challenge of inspecting full

color documents containing variable, personalized information to ensure that the

quality of the printed documents meet the needs of their customers.

Inspecting the image

To help such document services organizations address these quality controlissues, engineers at Videk (Fairport, NY, USA; www.videk.com) have developed a

vision-based inspection system specifically for the task (Figure 1).

The DocuVision 8600 inline system inspects full pages of colored printed material

in real time and at high speed to verify the print quality of the pages and the

integrity of the data printed on them. The system can be integrated directly

into printers from Canon-Oc (Melville, NY, USA; www.usa.canon.com), Kodak

(Rochester, NY, USA; www.kodak.com), Pitney Bowes (Stamford, CT, USA; www.

pb.com), Hewlett Packard (Palo Alto, CA; www.hp.com), Xerox (Norwalk, CT, USA;

www.xerox.com) and Ricoh (Malvern, PA, USA; www.ricoh-usa.com), or can be

placed downstream from a printer via a custom designed transportation stand

designed by Videk and manufactured by EMT International (Hobart, WI, USA;

www.emtinternational.com).

To inspect printed materials for errors and defects as they move continuously

along a web at speeds up to 200 ins/s, DocuVision captures images of each

printed document at a resolution of 200 dpi using up to four Piranha4 4kcolor line-scan cameras from Teledyne DALSA (Waterloo, ON, Canada; www.

teledynedalsa.com) that feature 4096 x 3 pixels, a 10 m pixel size and a

maximum line rate of 70 kHz.

Most lenses available today feature automatic focus and aperture and optimized

for the smaller frame size of digital cameras. However, for the DocuVision 8600

system, Videk chose to fit the cameras with F-mount 55mm manual focus lenses


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from Nikon (Tokyo, Japan; www.nikon.com) which are situated two feet above the

web along which the printed material travels (Figure 2).

The number of cameras deployed in the system depends on the width of the web

and the resolution of the image that is demanded by the application. A single 4k

camera for example, might be appropriate

to capture images from a 20in web at 200

dpi resolution, while a wider 42in web

would require the use of two cameras to

capture images at the same resolution.

Images captured from the line-scancameras are streamed over a Camera

Link interface to either a PC-based Karbon

or Neon frame grabber from BitFlow

(Woburn, MA, USA; www.bitflow.com),

depending upon how many cameras

are used. The frame grabber buffers

the individual lines from the camera,

reformats them as complete images

and transfers the image data over a

PCI Express bus interface directly into

the memory of the PC. There, they can

be accessed by the DocuVision print

inspection software for analysis.

To illuminate the web of paper, Videk

worked with Metaphase Technologies

(Bristol, PA, USA; www.metaphase-tech.com) to develop a custom lighting solution mounted in the optical pathway of

the camera. While conventional line lights illuminate a web from an angle, the

approach has the disadvantage that angled light can create shadows on slightly

rippled paper, with the result that any images captured cannot easily be analyzed.

Metaphase resolved this issue by projecting LED light onto the surface of a dome,

which then reflects diffuse light directly back onto the web of paper through a

slotted aperture.

Figure 2: To inspect printed materials for

defects as they move continuously along a

web at speeds up to 200 in/s, the DocuVision

system captures images of the printed

documents at a resolution of 200 dpi using

from one to six Piranha4 4k color line-scan

cameras from Teledyne DALSA.


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Most applications using line scan imaging require synchronization between the

moving object and the camera, and the DocuVision 8600 print inspection system

is no exception. By synchronizing the two,

the system ensures that the geometry of

the image will remain constant even as the

speed of the web changes. In addition, the

system must accurately identify a top of

form position mark on each page which

indicates the position at which the printer

started printing onto the page. Once the

mark is identified, it is used as a trigger

to initiate the capture of images from theline-scan camera.

The line rates of the Piranha4 4k line-scan

cameras are determined through the use

of an incremental encoder that is coupled

to a drive unit on the web. Data from the

encoder is transferred to a proprietary set

of hardware external to the PC dubbed

PageVision, which was developed to handle

all the I/O signals required for the interface

between the DocuVison software and

the printer hardware. The top of form

position mark, on the other hand, is detected by a small spot laser reflective

sensor which also transfers the data indicating the start of the document to the

same PageVision module.

Once acquired, the PageVision system feeds both sets of data into the PC hostover a serial connection which it uses to dynamically adjust the line rate of the

cameras and determine when the cameras should be triggered to start to capture

images. The captured images are then analyzed by the DocuVision software.

Aside from capturing and analyzing data on documents, the DocuVision 8600

system can be optionally fitted with additional lighting and cameras to detect

Figure 3: Aside from capturing and analyzing data

on documents, DocuVision 8600 can be optionally

fitted with a separate imaging system to detect

perforations in documents, such as those that

contain a check attached to printed material.


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variably-placed perforations in documents, such as those that contain a check

attached to printed material (Figure 3).

The perforation detection system backlights the perforation on the document

with a line light from Metaphase and captures images of the light that passes

through the perforation using one or two Teledyne DALSA 4k monochrome line-

scan cameras. The perforation images have a dark background with a white

foreground where light has passed through the holes in the perforated paper. The

data from the perforation detection camera(s) is also transferred to the PC over a

Camera Link interface to a frame grabber, formatted and passed to the PC where

it too can be analyzed by the DocuVision print inspection software.

During an inspection cycle, the images from all the cameras (both those

performing regular inspection tasks and detecting the perforation) are all

processed and displayed to the operator simultaneously. Therefore, any quality

defects, whether they are missing perforations or non-readable bar codes, can be

detected and either highlighted to an operator or flagged to stop the printer.

Software verification

Despite their obvious advantages, the widespread deployment of inkjet printers

has placed a new set of demands on manufacturers of automated image

verification systems. Besides checking documents for the accuracy of the data

printed on them, the image processing software must perform a range of

additional functions.

Written in C and running under a real-time Linux OS, the DocuVision color

print verification software uses a number of different software algorithms for

identifying features on pages of printed material. The specific modules for a

particular job are chosen through a configuration utility when the system iscommissioned at a specific printing house.

One feature of the system is its ability to determine whether any errors on the

page have been created by a printer whose ink jets have become stuck on or off

due to clogging. Jets that stick on cause streaking resulting in a continuous line

page after page while jets that become clogged can cause a color to drop out or

result in voids in page content.


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Since most modern documents are printed in color, the software also measures

the correctness of the color on the paper. Brand-essential colors such as those

found in a corporate logo, can be trained into the system and subsequently

monitored for the entire print job when each document is analyzed. In addition,

the software can be set up to read 2D bar codes, linear bar codes, and postal

codes, and perform optical

character recognition (OCR) to

ensure that the printed documents

contain accurate information.

DocuVision also checks the

registration of the cyan, magenta,yellow and black (CMYK) color

planes by inspecting a test element

such as a crosshair. If a color

moves out of register, the vision

system identifies the problem and

which color has moved. No less

important is the measurement of

the registration of the print itself

either in the vertical or horizontal

direction, which can be resolved to

an accuracy of 0.005ins.

One of the most important attributes of the software, however, is its ability to

perform conditional execution, or executing a sequence of inspection routines on

a document based on the artifacts that are found on the document. In that way,

printed documents comprising a number of different pages can be inspected in a

custom fashion according to the nature of the material printed on them.

Each document inspected by the system can be tagged as having passed or failed

any given vision inspection task. This data can be used to trigger the system to

produce a visual indicator on a display screen to alert an operator (Figure 4) or to

sound an alarm.

If the system detects a catastrophic error in the printing process, it can also stop

Figure 4: Each document inspected by the system

can be tagged as having passed or failed the vision

inspection. This data can be used to trigger the

system to store the information relating to that

document on a database and/ or produce a visual

indicator of which vision inspection failed to alert an

operator.


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one or more of the printers, eliminating the expenditure of further paper, ink

and production time. To do so, the DocuVision software delivers an instruction

to halt the printer to the external PageVision module which communicates the

instruction to the printer over an optically isolated output.

Tagged and tracked

When combined with Videks ReCon Manager data collection and reporting

software tool, the 8600 system can also collect and store data relating to the print

quality and document

data fields (such as check

amounts) on an SQL-based

database.

To do so, ReCon Manager

software accepts the

inspection results passed

to it by the DocuVision

system over an Ethernet

connection. A data

handshake protocol

between the two enables

the DocuVision system to

be aware that the data collection system is connected and will alert the operator

via a warning on screen if the connection is lost.

ReCon Manager compiles all data on the inspections performed by the

DocuVision system, and generates production reports based on customer-

specified requirements. It allows networked access - either on-site, remote or

mobile - to the production information and serves as a gateway for inspectiondata to be communicated to higher-level Automated Document Factory (ADF)

systems via Videks ADF Bridge module (Figure 5).

ReCon Manager compiles all data on inspections performed by the DocuVision

system and generates production reports based on customer-specified

requirements.

Figure 5: ReCon Manager compiles all data on inspections

performed by the DocuVision system and generates production

reports based on customer-specified requirements.


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Common reporting applications include the identification of missing or duplicate

documents, the tallying of the total amounts of check print jobs and comparison

with intended production totals. The system can also track color quality

tolerances, streaks or voids and bar code quality. Up to eight DocuVision systems

can be supported through a single Recon manager system, enabling reports to be

consolidated from multiple print lines into a single access point..

Not a Vision Systems Design magazine subscriber? Click hereto request a free

subscription.

LARRY WILLOUGHBY, Applications and Service Engineer, Videk (Fairport, NY,USA; www.videk.com)
http://www.vision-systems.com/https://www.sub-forms.com/dragon/init.do?site=PNW37_VZnew&pk=ED14https://www.sub-forms.com/dragon/init.do?site=PNW37_VZnew&pk=ED14http://www.vision-systems.com/


10/19Vision Systems Design:: EDITORIAL DIGEST

0

Originally published April 2014

Modular vision system eases

printed circuit board traceability

Line-scan cameras ease the task of reading barcodes

on multiple circuit boards in PCB panel.

by ANDREW WILSON, Editor

TODAYS PORTABLE CELL phones, tablets, and electronic devices require

increasingly smaller printed circuit board (PCB) footprints. At the same

time, installed semiconductor processing equipment such as screen

printers, chip placement systems, optical inspection units, and reflow

ovens have been designed to handle much larger PCBs such as PC motherboards.

To take advantage of this legacy semiconductor equipment while at the same

time increasing the throughput of smaller PCBs, manufacturers have turned

to a process known as panelization. Here, a number of identical circuit boards

are printed onto a large panel that can be handled by existing equipment. After

processing, these panels are then separated for final testing.

Unlike single motherboards that may require reading a single barcode, says

Steven King, Senior Solutions Engineer for Electronics at Microscan (Nashua, NH;

USA; www.microscan.com), each individual panel and each of the multiple circuit

boards that it contains must each have a unique barcode identifier. In this way,

each individual circuit board can be identified with each panel as the PCB panelmoves through the production process.

In this process, barcode labels (or codes laser marked onto the individual boards

within a panel) are affixed to the panel and individual circuit boards before the

screen printing process. To ensure that each of these panels and the individual

circuit boards they contain can be tracked though the entire process, these

barcodes must be read after they are affixed or marked.


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Modular vision system eases printed circuit board traceability

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Differing approaches

In the past, says King, this was

often accomplished by an operator

using a handheld barcode scanner -a

process that was time consuming and

subject to human error. To automate

this process, PCB manufacturers can

incorporate automatic barcode readers

that can read the panel and circuit

codes after they are affixed or marked.

One approach to performing thistask automatically, says King, is to

use an array of cameras or barcode

readers that are positioned over

specific areas of the board where the

barcode will be known to be affixed.

While this solution is effective when

large batches of the same product are

being manufactured it is not flexible

since, should a new batch of panels

with different-sized circuits need to be

processed, the positions of each of the

cameras or barcode readers must be reset.

To overcome this limitation, while at the same time increasing throughput and

eliminating human error, Microscan has developed a line-scan-based machine

vision system known as PanelScan (Figure 1). Capable of being mounted to most

in-feed or transport conveyors, PanelScan will be offered in two versions. Thefirst, PanelScan Standard, incorporates a single line-scan camera and is capable of

scanning PCBs as wide as 10 in while the second, PanelScan Wide, features a dual

line-scan camera combination capable of scanning boards of 18 in width.

Line-scan cameras

In the design of the PanelScan Wide system, two raL6144-16gm Racer line-scan

Gigabit Ethernet cameras from Basler (Ahrensburg, Germany; www.baslerweb.

Figure 1: Designed to read multiple barcodes on

circuits on PCB panels, PanelScan is a line-

scan based vision system with a throughput ofapproximately one board per second.


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com) are mounted on a gantry 13 in from the PCB. Both cameras are fitted

with an AF 60mm Nikor lens from Nikon (Melville, NY; USA: www.nikonusa.

com) that allow each camera to scan a 10 in swatch across the PCB as it moves

though the system. To ensure that the entire

18-in swath is scanned, each camera is

positioned so that the field of view of each

camera overlaps by 1in (Figure 2). This

configuration, says King, allows the system

to read standard barcodes as small as 3.3

mil or Data Matrix 2D codes as small as 5

mil.

To illuminate the PCB as it moves under

the cameras field of view, Microscan has

incorporated two of the companys own

NERLITE HI-BRITE LL-300 Series white line-

lights into the system. Mounted in an off-

axis configuration, these 300 mm lights are

butted together to form a seamlessly white

line-light that illuminates the PCB as it

moves under the field of view of the dual-camera system.

As a board moves through the system, its leading edge is detected by a retro-

reflective sensor from Tri-Tronics (Tampa, FL; USA: www.ttco.com), the output of

which is used to trigger the scanning process. Images are then transferred over

each cameras Gigabit Ethernet interface to a host PC. This data is buffered to the

PC in 256 line segments of each 6k x 1 scan. Transferring fifty of these 256, 6k x 1

line segments from both cameras results in an image of 12k x 12k x 8-bit pixels.

Image analysis

This data must then be processed to detect both the barcode on each panel and

the individual barcodes associated with each individual circuit board. To perform

this task, Microscan has incorporated its Visionscape machine vision software

package into the system. In addition to incorporating automatic identification

tools for decoding linear and 2D codes, the software also incorporates an array

of image enhancement and analysis tools. However, just as important as the

Figure 2: Two Gigabit Ethernet line-scan cameras

are used to scan an 18-in swath of the PCB as it

moves under the field of view of the system.


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software tools that are used to perform barcode detection is the graphical user

interface that Microscan has developed for the PanelScan system.

In the development of the GUI, says John Agapakis, Director of Americas Sales

at Microscan, it was necessary to provide an easy method of both configuring

the system and providing fast barcode reading without the operator requiring any

knowledge of machine vision software.

Specifically, each batch of PCBs panels may contain a number of different

circuits in an array of multiple rows and columns (Figure 3). While some panels

may contain twelve circuits configured in a 3 x 4 matrix, others may contain

many more. To identify which type of panel is desired to be inspected, the GUI

allows the operator to enter this matrix format before the panel is scanned.

After this data is entered, a single panel is scanned through the system in

teach mode. After scanning the complete image of the panel, each of the circuitboards is automatically processed to increase the contrast and the image

displayed on the GUI.

After this operation is complete, the operator highlights the center portion

of the top left and bottom right barcode within the image. The system then

automatically searches in all the regions for the barcodes located on each of

the individual circuits and reads each individual barcode. Data from all of the

Figure 3: Once trained, the

locations of each of the

barcodes on each individual

PCB are identified, read andstored as a concatenated

string.


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Machine Vision Adds Traceability to Packaging

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marks placed on them by an

operator to indicate the number

and variety of produce within.

At New Leaf Produce, Mike Jost

required a system to place a

traceable barcode label on cases

of its stone fruit. Jost approached

Vision Sort to develop an in-line

vision-based system that can

identify the type of case, produce size, and number

of products packed (see Fig. 2). The data are thenused to generate GS1-128 barcode labels that are

affixed to cases as they travel along a conveyor at

approximately 60 boxes/min.

Vision Sort has developed an in-line vision-based

system that can automatically identify case types

by the identification marks on them that are used to

indicate the number and sizes of products within. The data are then used to affix

an individual barcode to each case.

Smart vision

As a case of produce moves under the inspection system, its presence is detected

by a photodetector from Banner Engineering, which triggers a pair of 12-in.

LC300 LED strobe lights from Smart Vision Lights positioned at a 30 angle and a

monochrome 2-Mpixel, 2/3-in. format, 50 frames/sec ace camera from Basler.

Images from the camera are transferred over a GigE interface to an Intel-basedmulticore PC. To identify the types of cases, Gaddy used the HALCON 11 vision

software package from MVTec Software. For the HALCON software to identify

the boxes of produce, the system must first be trained. Images of each type of

box to be identified are first captured as they travel through the system, and

shape model files are created by analyzing the physical dimensions of the box

and artwork printed on it (see Fig. 3). In practice, some boxes require as many

FIGURE 2. Vision Sort has

developed an in-line vision-

based system that can

automatically identify case

types by the identification

marks on them that are used

to indicate the number and

sizes of products within. The

data are then used to affix an

individual barcode to each case.


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as six shape models per box to be captured by the system before one box can be

distinguished from another.

Shape models of the cases are then compared with previously trained models to

rank, or score, the potential matches that are found. All models that are found to

have a score above a set minimum are then run through a scoring algorithm that

ensures the correct case is identified by the software. Should two cases appear

similar in all but color, a grayscale analysis is performed on the image to make

the distinction between cases.

Once the case type has been identified, the location of marked checkboxes is

analyzed to determine the number and size of the fruit in the case. In instances

where the produce type in the cases has been defined by placing a sticker on thecase, or manually stamped, an optical character recognition (OCR) function reads

the characters.

The system can search through more than 100 shape models and can classify the

case type and determine which checkboxes have been checked by the packers

in about 65 msec, after which a label is printed and affixed to the case. The total

time taken to identify and affix a label to a case is approximately 0.5 sec.

FIGURE 3. Images of cases

are analyzed by a PC to

determine the type of

box and the nature ofthe contents within. The

data are combined with

additional information

about the grower,

packing facility, and

date it was packed

and used to generate a

unique barcode.


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After the model of the case has been identified, a CLV620-0120 barcode readerfrom SICK reads a barcode sticker previously affixed to the back of the case

to identify the packager of the produce. These data, together with the box

identification data, are logged into a database and can be recalled later for

productivity, report generation, or payroll purposes.

Having identified the case type, size, and number of items of produce, the data

are used to create a barcode identifier label. This is transferred over an Ethernet

link to a S84 print engine from Sato that prints the barcode label, which is affixed

to the case by a 250 label applicator from IDTechnology.

System control

A graphical user interface (GUI) written in Microsoft Visual Studio C# enables

the user to control all the parameters of the system from a single touch-panel

and handles the interface to the vision inspection software, the label printing

and application tasks, and data logging, report generation, and alarm handling

functions (see Fig. 4).

In addition to identifying the cases of produce and applying a barcode label,

the system also maintains a Microsoft SQL relational database that contains

parameters such as where the vision software should examine images for the

checkboxes on each type of case and at what location the barcode should be

placed. The software can also generate Excel files on demand, which contain

pertinent reporting information such as system statistics, worker productivity,

piece rate tallying, and box totals.

FIGURE 4. All the parameters of the

system can be controlled from a

single touch-panel interface that

presents the user with access to thevision inspection software, label

printing and application tasks, data

logging, report generation, and

alarm handling.


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Custom Visual Studio C# software also monitors critical system parameters, such

as whether the printer is low or out of labels. If these parameters exceed alarm

levels, a text message is sent to maintenance personnel.

Due to the variety of different-sized cases that travel down the conveyor, it

is important that the system be able to position the barcode label at specific

locations according to the type of case. A custom-built positioning system aligns

the boxes vertically and horizontally in front of the label application tool so they

can be affixed in the exact position.

Future models

Although the systems that have currently been shipped use just one camerato identify and label the cases, future systems will employ two, or even three,

cameras to further increase the functionality of the system. For example, a

second camera will capture an image of the front of the cases as they move down

the conveyor, enabling labels affixed to them by the packers to be automatically

identified. A third camera placed in the hood of the vision system will capture

images of the fruit in open cases. These images can then be analyzed to identify

what type of produce is contained in them, obviating the need for packers to

physically mark the checkboxes on the cases.

The Vision Sort system was developed to minimize the impact to the users

process and be fast enough that the average packing operation would only need

one system per packing line rather than several systems. Two of the current

single-camera systems have been in use since June 2012 at New Leaf Produce.

Additional units were installed later in the summer of 2012 at two other

California grower-shipper facilities. Multiple camera systems are expected to be

shipped to customers during the course of 2013.

Not a Vision Systems Design magazine subscriber? Click hereto request a free

subscription.

GARTH GADDYis president at Vision Sort (Reedley, CA, USA; http://visionsort.org).
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Deploying Ocr Systems in Industrial Manufacturing.whitepaperpdf.render