The Difference Between Optical Character Recognition (OCR) and ID Scanning Software

On a daily basis our sales team gets a call asking for an OCR Scanner. Although to many this makes sense, to us in the industry it does not really exist. I am writing this blog to help our clients and the public understand the difference and help you the reader on your quest to understand the imaging and OCR industry.

So let's get the terminology straight. A scanner is a piece of hardware that scans various documents, turns them into an electronic image so we can store it digitally on our computer or a server. A scanned image is only a picture you cannot do any actionable or meaningful data manipulation on a scanned image since it has not passed through an OCR Engine. OCR which stands for Optical Character Recognition is the process of reading that document and extracting and digitizing every word. Once the data is extracted from the image we now have an advanced powerful tool that saves time, money and greatly increases productivity.

In the past, in order to enter information into a database or online form all had to be done manually. You probably heard of overseas teams that conduct data entry, it even used to be a full time job position. Companies that were overloaded with paper would send it overseas to a company that would have hundreds of employees who are paid to look at the document and enter the information into specific boxes on an electronic form. This task was labor intensive and very expensive to do but its a very important part of getting client information. Especially in Healthcare where if the information is not put in correctly people may not get the care they need.

So to sum it up OCR is the technology behind converting printed or handwritten text from images, PDFs, and scanned documents into digital, machine-readable text. For businesses, OCR means transforming paper-based information into searchable data, which is critical in today's digital world.

Some Examples of How OCR is used

Medical Field:

Medical Research: OCR extracts data from scanned research papers or clinical trial documents, enabling researchers to analyze and organize large volumes of text efficiently.

Digitizing Patient Records: OCR is used to scan and convert handwritten or printed patient forms, medical histories, and prescriptions into digital formats for electronic health records (EHRs). For example, hospitals use OCR to process industry forms like CMS1500 (HCFA), UB 04, Dental Claims and many other forms, making patient data searchable and easier to find and manage.

Prescription Processing: Pharmacies employ OCR to read prescriptions, reducing errors in interpreting medication names and dosages, which improves patient safety. Sometimes this can be challenging with handwritten prescriptions.

Financial Field:

• Invoice and Receipt Processing: OCR automates the extraction of data from invoices, receipts, and purchase orders. For instance, accounting software uses OCR to capture vendor names, amounts, and dates, streamlining expense tracking and bookkeeping. A good OCR system can extract each line item detail on an invoice and make mathematical calculations as well as correct any misspelled information.
• Check Processing: Banks use OCR to read handwritten or printed checks, extracting details like account numbers, amounts, and signatures to process transactions quickly and accurately.
• Document Verification: OCR helps verify financial documents like tax forms or loan applications by extracting and validating data, reducing manual entry errors and fraud. Data extracted into each field can be  cross referenced and checked for accuracy with information that exists in the company's database thus ensuring total accuracy of information going into the system.

Additional Application - Legal Field:

• Document Management: Law firms use OCR to digitize contracts, case files, and handwritten notes. For example, OCR converts scanned legal documents into searchable PDFs, allowing lawyers to quickly locate specific clauses or evidence during case preparation.

Through these steps, OCR software systems translate physical text into digital data, helping to facilitate document and information management across many sectors. This not only saves time and labor costs, a good OCR system automates a process from start to finish in the most accurate and efficient way saving companies time, money and allowing employees to focus on more sophisticated important tasks instead of simple data entry.

Emerging Trends in OCR and ID Scanning Software

Integration with AI and Machine Learning

AI and machine learning are revolutionizing OCR technology by increasing accuracy and adapting to diverse text formats and languages. These advancements make OCR more powerful and add abilities such as detect fraud using pattern recognition, predicting outcomes based on information in documents, self learning and more.

Example: AI-powered OCR can recognize handwritten text and complex fonts, while AI-enhanced ID scanners detect counterfeit IDs more effectively by identifying irregularities in document structure.

Factors to Consider When Choosing Between OCR and ID Scanning

When selecting OCR software, businesses should consider:

• Accuracy Requirements: OCR is ideal for document scanning since it can retrieve general text. .
• Security Needs: When it comes to document management, OCR is effective. However, when dealing with sensitive information, ID scanning software is recommended. 
• Industry-Specific Regulations: Compliance with rigorous standards in banking and healthcare often requires advanced functionality that very few OCR systems can do efficiently.

For more information about our products and solutions , feel free to reach out to us.

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