In a world of digital processes, it’s often difficult to imagine a time when society relied solely on paper documents and handwritten records. Even as electronic and mobile technology moves forward, manual and paper-based files are still an essential part of our daily lives.
Fortunately, when there’s a need to transfer and translate paper documents to digital versions, technology provides several options. Optical character recognition (OCR) is one solution that helps users scan and import handwritten documents into usable electronic files.
In this post, we’ll explain more about OCR systems, share modern use cases for multiple industries, and discuss the advantages that make this technology worthwhile.
What is optical character recognition (OCR)?
Optical character recognition (OCR) is a method of distinguishing letters and characters in physical text and encoding them into a digital format. The handwritten or paper document is scanned either electronically or mechanically. OCR is the process by which the original text is read by the computer system.
In layman’s terms, OCR might simply be referred to as “text recognition.” This is a simplified way of looking at the end goal of an OCR system.
What is OCR technology?
OCR technology refers to using optical character recognition to solve real-world problems.
Moreover, OCR technology has its own problem-solving capabilities. This is especially true when the physical source document is difficult to read, damaged, or compromised. Powerful and smart OCR technology should be able to overcome these challenges and interpret the characters to make them both readable and usable.
Depending on purpose or need, experts and designers can tweak the capabilities of OCR to make them even more powerful. In OCR systems, optimization is valuable because it improves character recognition and is capable of handling unique and rare images.
OCR systems can range in complexity from very basic to extremely intuitive. Complexity is generally based upon the end goal of the program, the security requirements, and the types of documents that are involved.
How does OCR work?
To fully leverage the power of OCR technology and systems, users must have access to a two-part mechanism that makes text recognition possible.
Hardware – The first step in any OCR system is most often a digital scanner or file reader that scans the physical document. Depending on the age and condition of the document, OCR experts may use specialized tools in order to preserve the text and prevent further wear and tear.
Software – The second step of the OCR process involves the software or a computer-based mechanism that reads, translates, and imports the document itself. This is the part of the process that makes the physical text machine-readable. OCR software generates a “soft copy” version of the file, usually in the form of a PDF, digital document, or image.
Once the physical document has been scanned and received, there are two mechanisms by which the physical text is translated.
In a pattern-based OCR system, the computer model compares a scanned text file to the data that it already knows. To set up a pattern recognition system, users must feed examples to the software composed of common letters, characters, and symbols.
Then, once the computer receives a real file, it uses that preloaded data to scan the physical document and distinguish results from the available patterns.
Feature detection is similar to pattern recognition, but it relies on the ability to pick out key features of letters and characters. For instance, a capital letter ‘B’ has the features of a single straight line connected to two rounded lines. A feature detection system has this information on file for every individual letter or character that it knows how to identify.
With this data in mind, feature detection systems scan the physical text and separate blank background color from character features. Then, it translates the recognizable features into digital versions.
In some OCR instances, the scanned results are converted to ACSII, or the American Standard Code for Information Interchange. This computerized language is common for text-based computer files that include alphabetic characters, numerals, or special symbols.
ACSII text files assign binary codes to each individual number or letter. By doing so, the computer system is able to recognize and use the text files. As it relates to OCR, ACSII is simply the language of translation that happens behind the scenes.
Modern OCR applications and use cases
Whether we realize it or not, many of us have interacted with and benefited from optical character recognition at some point in the course of our typical routines. Common OCR use cases improve daily life and business, even when they go undetected.
Below are some of the most relevant and widespread uses for optical character recognition. This list is not all-inclusive, and the potential for OCR expansion is high.
With optical character recognition, manual data entry is no longer the only way to read and upload physical texts and documents. For teams and departments buckling under the weight of administrative burden, OCR can alleviate a significant amount of that pressure.
Data entry relief is relevant for nearly any industry or type of organization that collects and stores information from customers and staff members, but specifically impactful life-saving industries such as supply chain logistics and healthcare.
Finance and banking
In the financial realm, OCR is already used to read physical checks and deposit them into corresponding bank accounts without the use of a teller.
ATM machines also read and interpret checks and money to deposit the correct amounts. This technology provides flexibility and convenience to busy customers who crave secure, reliable options.
Optical character recognition also has several applications for education. Not only is OCR helpful for educators and graders when it comes to automation, but it also serves an extremely impactful purpose by helping students with dyslexia or learning disabilities. With text-to-speech technology, students who require verbal processing can benefit from more options and greater accessibility.
Postal and mail services
One of the most common ways that OCR makes modern life easier is for postal and shipping services. Optical character recognition empowers the process of reading addresses, sorting mail for delivery, and identifying personal information. Without this technology, it would take a significant amount of time to sort, send, and deliver important mail to both homes and businesses.
How does OCR relate to artificial intelligence?
At its foundation, optical character recognition is not an AI-based technology. OCR can exist independently and serve its own purposes.
That’s not to say, however, that there is no potential for AI development. In fact, OCR is a perfect example of a technology that could be enhanced and improved by the addition of artificial intelligence or machine learning.
In the future, AI may be useful for developing even more advanced OCR systems that are capable of reading additional types of text and handwriting. Certain text styles, languages, and patterns could be stored and interpreted by an AI-powered OCR system. Additionally, artificial intelligence could be used to make the entire process more intuitive and predictive, which could eliminate even more time and promote better results.
Benefits of OCR
The use cases above illustrate the power and possibilities of OCR technology. If the practical applications weren’t enough, there are many advantages to using optical character recognition.
It saves time by eliminating the need for tedious manual data entry.
With OCR, it’s possible to import large amounts of text at one time. The scanning process is often fast, seamless, and efficient.
It provides a way to preserve and protect physical documents that could otherwise be lost, damaged, or mishandled. Digital file versions act as safeguards in the event of loss or human error.
Many scanners and hardware devices produce clear, high quality images that can be used in a variety of ways.
OCR can replace paper-based forms, applications, and administrative needs that are unreliable, slow, and risky.
Are there any disadvantages to OCR technology?
As with any system, there are some downsides to consider when using OCR technology. Many of these negative aspects are mere inconveniences that could be eliminated with further development.
OCR is not foolproof, meaning that manual proofreading and correcting are often required to ensure total accuracy.
Some systems are not equipped to handle handwriting. In these cases, an OCR system can only read electronically printed material.
Translating and scanning large quantities of files may require large amounts of computer storage and backup.
Depending on the length of text, it may be more cost-effective to read and import manually. OCR is an investment and most useful when there is a substantial amount of information to scan and read.
Reminders and takeaways
While text recognition software might not have the bells and whistles that other types of technology or artificial intelligence possess, the use cases are extremely practical and reliable. Optical character recognition saves valuable time, effort, and resources and provides a pathway for older data to be read, understood, and analyzed.
OCR also holds great potential for the AI community, as its intuitive and predictive features are only on the cusp of development. For individuals who have an interest in optimizing OCR for AI-based applications, the stage is set for tremendous innovation and creativity.