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Optical Character Recognition & Optical Character Verification in Pharma Industry
- Didier Lacroix, Senior Vice President, Cognex Corporation
The pharmaceutical industry has been compelled by government regulations to adhere to standardised solutions across all production and packaging operations. As the challenges become greater and the stakes higher, pharmaceutical product manufacturers need even more sophisticated machine vision hardware and tools to stay compliant with regulations, ensure customer confidence and mitigate risks. At the same time, these tools need to be easy to use and deliver even more reliable and repeatable results.

The Optical Character’s powerful algorithm prevents misreads, handles process variations and provides easy font management. It’s fast, easy to set up and simple to use across all platforms with minimal training being required.

Regulations Worldwide Drive the Need for OCR
Barcodes are a traditional solution, but consumers cannot read. Hence manufacturers are turning to optical character recognition (OCR) technology using vision systems that can read alphanumeric text. Machine vision systems with OCR tools provide four functions for pharma operations processing and packaging operations:

1. Presence/Absence: To check that product descriptions and tracking text have been printed on the product.

2. Track and trace: Reading of every alphanumeric text written in the content, based on the data which is placed in the system

3. Verification: Verifies each and every alphanumeric text, and identifies the mismatch. eg, It verifies whether alpha numeric print is done or not on the product

While the pharmaceutical industry has deep experience with OCR/OCV applications driven by government regulations that require standardised solutions across all production and packaging, most customers do not use standardised fonts, software or hardware. Seeing the growth in number sorting and tracking applications, Cognex engineers realised that they needed to redesign their existing OCR/OCV tools to:

• Learn and read any printed font;
• Read text even when there is little contrast between type and background;
• Read text even when there is significant variation in width and height;
• Read text when letters are touching, skewed, and distorted; and
• Differentiate between similar shapes, such as the letter “O” and the number “0”

OCRMax Achieves Automated Character Reading Accuracy Rates Above 99 per cent
The exceptional performance of OCRMax in comparison to other OCR/OCV tools is based on several factors, most notably better approaches to image preprocessing, segmentation, classification, a dual-verification process, fielding and font training and management. When combined together, these features give users the chance to optimise the OCR/OCV for millisecond character reads, 99.99 per cent read rates, or anywhere in between.

According to the above images, OCRMax easily handles a wide variation of character appearances some doubt whether the character is a letter B or number eight (8). Fielding rules programmed by the user give OCRMax another way to determine the proper character value. Fielding functionality featured in OCRMax allows wildcards, and works with defined variable length strings (this serial number should be between three and five characters, for example) as well as fixed length strings.

While many OCR/OCV tools have fielding capabilities, OCRMax is the only tool that can use fielded strings in both fixed and variable length character sets. As an example, a variable length character string may have the year embedded in it, but the location varies depending on the product and lot number. Using the Fielding tool, OCRMax will read the character string and then search for the expected year code within that string, regardless of the overall length. If the year is not located, OCRMax will “fail” the character string based on the customer’s preset Fielding rules.

Usage of OCR in Pharma Industry:
1. OCR ensures code presence and readability before products exit the factory:
Machine Vision helps to verify that required text strings make it onto the product or packaging. For instance, inkjet printers are commonly used for marking date codes, batch codes and expiration dates in many packaging applications, due to their ability to print variable information at very high speed. However, print quality can degrade over the course of process runs, resulting in inconsistent codes or no code at all. Without a system in place to confirm the presence of the code, a printing fault - such as a clogged nozzle, interference from debris, or depleted ink - may affect print quality, and this error could go unnoticed until later in the process. This result to increased downtime, costly re-runs or worse: if the product makes it out of the factory without a required code, it will need to be scrapped or recalled.

OCR reads a code to determine its presence, whereas OCV (Optical Character Verification) recommends for confirmation that a code will be readable after it leaves the plant. OCV-based inspection is most often used to verify that the printed codes will be of sufficiently high quality to be legible throughout the supply chain in the event of a product recall – of particular concern in the pharmaceutical industry.

Absent or unreadable codesare unacceptable in this highly regulated industry. Machine vision provides manufacturers with the peace of mind that their products are properly marked before they make their way into the supply chain.

2. OCR tracks products throughout the Supply Chain:
The traceability through every step of the manufacturing process is critical across all industries where manufacturers are required to comply with safety and anticounterfeiting regulations.

OCR reads barcoding, lot coding, batch codes, expiration dates and serialisation numbers. An OCR application can be programmed to compare the actual text with an expected string, as defined in the database, and flag any missing or outof- sequence serial numbers. Barcodes and OCR are frequently used together to achieve maximum reliability of the data collection process. Reliable product tracking and data management is essential for this industry. It also helps in preventing diversion of goods to so-called “gray market” vendors.

3. OCR Matches Labels to Products:
Mislabeling has severe implications to both manufacturer and consumers. OCR helps to ensure accurate labeling to all the products. Manufacturers must accurately state the contents of an item on its label or packaging, or face severe consequences, such as governmentimposed penalties, costly recalls, and diminished brand perception. One of the most common reasons for product recalls - mislabeling - has serious implications for both manufacturers and consumers, ranging from customer dissatisfaction to safety risks. OCR is highly effective in applications where multiple character strings, such as sequential numbers are presented to the system. In applications where all the contents are expected to be the same, OCV may be recommended; in these cases, the vision system does not read the characters, but instead verifies that they match an expected string.

Machine vision automation eliminates human error due to fatigue and distraction, resulting in improved accuracy and increased throughput.

How to evaluate OCR technology in a vision system
Questions in consumers’ minds while evaluating OCR software:
? Can the OCR software read any printed font?
? Can it read text when there is little contrast between the text and background (colored text or background noise), with a lot of letter-to-letter variation, skewed letters, or touching letters?
? Can it read text strings that are poorly printed, scratched, or with washed-out characters?
? Can it read text regardless of surface type, including glass, metal, cardboard, ceramic, and plastic?
The future of OCR-enabled vision systems in the pharma industry
The pharmaceutical packaging market is constantly advancing and has experienced annual growth of at least five percent per annum in the past few years. With the strict rules and regulations that are being adopted and implemented in the industry to stop drug counterfeiting, it is seen that the drug manufacturers are taking effective measures in their production line to bar the same.