What is Optical Character Recognition (OCR)?

Support by sharing this article on your social media networks

Last Updated on 4 days

In this digital world, optical character recognition has become an essential element in any organization digitization initiatives. OCR is typically used in business applications to capture structured information from documents and convert it into digital format for archiving, storage, and retrieval.

Optical character recognition (OCR) is a computer-based technology that converts images of text into text. The process typically involves the use of an optical scanner, which scans the image and converts it to digital data.

The resulting data can be used in a variety of ways, including for example, searching for words and phrases in large amounts of scanned documents or creating digital copies from printed pages.

OCR is typically used in businesses with large volumes of paper documents such as insurance companies, banks, libraries and government agencies.

OCR software can be utilized to scan physical documents and convert them into digital files. This can help speed up the process of digitization and make it easier to search through the document later on.

In this article, we will define optical character recognition, discuss its importance, advantages, usage, and speculate on its potential.

serious female office worker using printer in workplace
Photo by Andrea Piacquadio on Pexels.com

What is OCR?

Optical character recognition (OCR) is a method of converting images of typed, handwritten, or printed text into machine-encoded text. OCR can be used to help digitize text from old books, documents, and other sources. This process can help make the text more accessible and searchable, and it can also help preserve the original formatting of the text.

OCR technology aids in the automation of data extraction from typed or written text in a scanned document or image file and then translating the text into a machine-readable format for data processing such as editing or searching.

It allows a large range of paper-based documents in a variety of languages and formats to be digitized into machine-readable text and improves information accessibility for users.

OCR processing employs a mix of hardware and software to turn paper documents into machine-readable text.

Prior to the invention of optical character reader technologies, the only way to digitize handwritten paper documents was to manually retype the text.

In the 1990s, when digitizing historical newspapers, OCR technology became prominent. However, technology has progressed considerably since then, and more sophisticated methods such as artificial intelligence and machine learning are now used to improve accuracy.

Feel free to check this timeline for historical information.

Optical Character Recognition Use Cases

OCR is frequently utilized as a hidden technology, powering a wide range of well-known systems and services in our daily lives.

OCR can be used for a variety of applications, including:

  1. Scanners for advanced QR codes
  2. Data input for commercial documents such as cheque, passports, invoices, bank statements, and receipts
  3. Recognition of license plate numbers
  4. Patient paper form submission
  5. Digitization of hard copies/ books
  6. Document classification
  7. In airports, for the recognition of passports and the extraction of information
  8. Translation into another language

OCR is typically used in businesses with large volumes of paper documents such as insurance companies, banks, libraries and government agencies.

Banking

One of the most OCR use case can be found in the banking sector.

The banking industry is a large user of this technology. For instance, we utilize it when we deposit checks in ATMs. Checks are automatically scanned to recognize the amount, signature, and the depositor and it is all done without any human intervention.

  1. The check, which was handwritten, is scanned.
  2. Information is converted into digital text.
  3. Signature is validated.
  4. Real-time clearance.

Healthcare

Healthcare is another OCR use case. Every year, hundreds of millions of medical claims are filed, which can result in a significant amount of paperwork and manual processing.

To go paperless and improve patient care, healthcare institutions are leveraging optical character recognition software.

Optical character recognition facilitates the submission and retrieval of medical records, claims, EOBs, and virtually any other medical document.

In addition, it helps institutions comply with HIPAA’s security regulations.

Legal professionals must have rapid access to and retrieval of information. To achieve this aim, the majority of large and well-known law firms have either begun or are in the process of digitizing their massive paper documents.

It is critical to turn these scanned papers into searchable ones by digitizing and utilizing this powerful technology.

The optical character reader will ensure that they can quickly discover any resource by searching for keywords inside the document’s text.

Which Type of Device Is An Optical Character Recognition?

OCR recognizes text in pictures and converts it into machine-readable text using a mix of hardware and software. Text is read using hardware such as an optical character reader (scanner). An optical character reader is a device included in most computer scanners that collects visual information and translates it into digital data that the computer can display while software generally does complex processing.

Features of Optical Character Recognition

There are several features of Optical Character Recognition, or OCR, that make it useful for a variety of tasks. OCR can be used to digitize printed documents, convert images of text into editable text files, and even recognize hand-written text. OCR is often used to digitize documents so that they can be stored electronically.

This can be helpful for archival purposes or for making documents more easily accessible. OCR can also be used to convert images of text into editable text files. This can be useful for tasks such as converting a scanned document into a Word document.

OCR can also be used to recognize hand-written text. This can be helpful for tasks such as converting a handwritten note into a digital text file.

The 4 top features of optical character recognition are:

  1. Ability to convert images of text into editable text
  2. Accuracy
  3. Ability to convert text from a range of different languages
  4. Fast processing speed

Optical Character Recognition in Content Management

While document management software should have many sophisticated capabilities, optical character recognition is regarded as one of the most important.

Have you ever wondered how document management or ECM solutions locate information while targeting a keyword in a document’s content?

With the help of this technology, when you search for a certain term, the system will return all the documents that fit the criteria based on their metadata or content.

Top content management companies have incorporated OCR technology into their platforms to convert scanned paper documents, PDF files, and images into editable and searchable data.

The system uses an optical character reader to recognize and interpret the text in documents in various languages and formats. This ensures that when you search for a certain keyword in the DMS or ECM system, the search results will return documents that contain the keyword.

It happens even though you aren’t aware of it! When a user imports a document into the system, it will automatically generate a searchable version and attach it to the document.

Employees would waste a lot of time if they didn’t have this capability. Consider what it would be like if an employee had to sift through stacks of paper to find the one they wanted!

Another benefit would be that employees no longer need to manually review documents or purge outdated records. Instead, by converting scanned text into editable text, document retention and preservation can be completely automated.

The intelligent automated data capture and use of it in the document implies that a more efficient method is used to assist users in quickly locating resources. The function of optical character recognition in automatically recognizing these critical data and inserting them as metadata into the imported document is important.

Nowadays, most companies require a means to redact or conceal essential information, such as personally identifiable information (PII), from unwanted access. Leveraging the power of AI can automatically recognize this type of personal content, redact it, and only reveal it to authorized persons.

The Future Of Optical Character Recognition

Today, intelligent OCR is seeing an unparalleled change as a result of the use of Artificial Intelligence techniques. It has evolved from a traditional image-to-text conversion technology to a human error checker.

AI is a tremendously effective tool for overcoming the limitations associated with classic approaches and producing far more accurate results.

Companies are beginning to look to AI-powered alternatives to increase productivity and extract meaning.

Combining optical character reader with AI will allow organizations to capture data intelligently and also understand their content. That means that AI technologies can search for mistakes without the need for human intervention.

As discussed previously, it will also help find sensitive information (PII) and automatically redact it to make it accessible to authorized personnel.

How do you think AI can help organizations in effectively capturing data?

What is Optical Character Recognition?

By definition, Optical Character Recognition is an electronic or mechanical conversion of the typed, handwritten, or printed text images into machine-encoded text.

Why OCR is Important?

It originated as a distinct and accurate digitizing solution, and it is now used by a wide range of industries.

This technology is used in a wide range of enterprises that face information management issues like as data loss, inaccuracy, and storage.

OCR Benefits

  • Boost Productivity
  • High Accuracy
  • Powerful Data Security
  • Storage Space
  • Enhanced Customer Service
  • Reduced Costs
  • Disaster Recovery

Leave a Reply