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Tech Papers

Effectively applying OCR

by Jeff Schmitz - Datalogic USA, Inc.

What is the difference between OCR and OCV?
People often intermix the terms OCR (optical character recognition) –optimally used in identification and traceability, and OCV (optical character verification) – optimally used to verify correct content and quality of text print.

OCR – Optical Character Recognition is a function that allows a vision system to “understand” human readable code. It is the translation of typewritten or printed text into machine-editable text.  Here, the vision system uses a stored library of images to compare individual characters or strings of text to and then subsequently decides what is printed. It is the equivalent to a human asking “What is this word?”

OCV – Optical Character Verification is a function that grades the quality of human readable typewritten or printed text. In this case the vision system checks the character or string against a known, trained pattern and grades the quality of the match. Typically, the higher the match score the greater the confidence that the inspected word is the trained word. This is the same as a human asking “Does this word match another word?”

Why manufacturers invest in Machine Vision OCR

OCR/OCV serves 2 overall functions in manufacturing:
Inspecting for correct print – both content and quality [OCV]
Identifying parts or components (sorting and assembly checking) [OCR]

Industry experts point to Machine Vision’s (MV) OCR function as a valuable tool in the important objectives of
mistake-proofing</li>
simplifying processes and reducing cost

Major ROI or business justification reasons customers choose MV OCR include:
Revenue stream protection: Prevent revenue loss – incorrectly marked parts are often rejected by major
   customers resulting in costly returns, costly rework and even customer loss.
Decrease liability risks and cost – incorrectly marked packaging can cost money, customers, and even lives.
Improve Productivity & save $’s
        -  Increase process efficiency. A good OCR tool will eliminate the human factor and provide guaranteed
           reliability. An example would be 100% reliability in product labeling.
        -  Decrease process complexity. Manufacturers can save additional coding and marking costs, OCR
           allows human-readable information on packages to also be used for part identification and tracking
           during the production process.
Increase customer satisfaction and expand customer base – Error proofed automated processes with MV
   OCR doing 100% inspection meet vendor requirements of demanding large customers.

OCR Target market segments and Industries:

Pharmaceutical – Marking on tablets and packaging is critical not only for consumer safety and regulatory compliance, but also for anti-counterfeiting. Typical applications are:
Expiration date verification
Lot code and batch verification
Mold cavity print, for example print within a bottle top
Label placement on bottles or packaging

Food and Beverage
Date code accuracy and legibility
Label verification
Expiration date verification
Lot code and batch verification
Mold cavity print, for example print within a bottle top
Label placement on bottles or packaging

Automotive and discrete component manufacturers
VIN tracking
component sorting
Label verification
Lot code and batch verification

Why OCR from PPT VISION?

Competitor’s machine vision OCR tools all operate fine in laboratory evaluations, but where they begin to have trouble is in the industrial world of high-speed print. PPT VISION OCR stands out by reading challenging real-world dot-matrix print, at varying speeds with less-than ideal lighting. Consult with a PPT VISION application engineer about solving your customer’s OCR challenges and learn first-hand how IMPACT repeatedly beats the competition with superior character scoring, speed and flexibility in applications requiring OCR.

One key reason PPT VISION wins is IMPACT's OCR algorithm with built-in thresholding and segmentation that rapidly reads through a library of individually taught characters, unlike competitor libraries made up of merged synthetic characters. A second reason is that in applications with challenging substrates and print medium, pre-processing tools can be used to improve character readability. The powerful image processing tools that are standard in IMPACT are not available on competitively priced smart cameras (only available in higher end vision software, typically more than $10,000 per camera).

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