Have you ever been in the middle of reading a textbook or an essay and wished you could use CTRL+F (or CMD+F) to search it like you would on a computer?
We all have. Manually searching for keywords or a specific sentence in a lengthy text is like looking for a needle in a haystack. Not having the option to automatically sort or find key information leads to a lot of wasted time, potential mistakes and headaches.
But never fear! OCR software can help digitize all kinds of documents for your convenience. OCR makes it possible for you to keep all the important papers and documents you collect as a person or a business without requiring the physical space to store them all.
What is OCR?
Humans are capable of recognizing the written word no matter how it is presented; we don't know the difference. But computers don’t work that way. Computers require machine-readable text to recognize and process text-based information. The characters in an image aren’t readable by a computer since they’re processed the same way as any other part of the image.
That’s why even though PDFs look like regular text documents, computers can’t always copy text from them. The text in a PDF is part of the image itself, rather than distinct pieces of information readable by a computer.
OCR, or optical character recognition, is a type of technology capable of recognizing the text inside images like scanned documents, PDFs, and photos. OCR software “reads” the text in an image and turns it into machine-readable text.
How does OCR work?
OCR software is only part of a larger OCR system composed of other software and hardware components. OCR software is capable of recognizing text in images that originate from scanners, cameras or PDF generators.
There are two types of algorithms that OCR software can use to recognize text within an image:
- OCR software that uses pattern recognition looks for patterns based on examples of text it has already been given. These examples can be in a variety of fonts and formats so the software has numerous examples to refer to. The software will compare images to patterns fed to it and pick out text in images if it finds shapes that match its references.
- OCR software using feature detection relies on a given set of rules for each character that enables it to recognize those characters in a document. A character has a number of rules associated with it, like straight lines, angles and shapes. The software will analyze a given image and use these rules to parse text character by character.
Once the image has been created, there are still steps that need to be taken before OCR software can begin parsing text from it. Broadly speaking, there are three basic steps to the OCR process: pre-processing, first pass and second pass.
Before an image can be analyzed, it has to be optimized so the OCR software can easily discern the text from the rest of the background. This touch-up step is called pre-processing, and as the name implies, it involves processing an image before it’s analyzed by OCR software. This step includes making edits to an image, like straightening it, removing blurs or artifacts from low-quality scans, adjusting contrast and sharpening the text.
For images such as scanned documents or pages, the pre-processing step also involves creating a two-color (or black and white), version of the image. The black areas will be recognized as potential text while the white background is ignored, further increasing the OCR software's accuracy.
The first pass
While some legacy OCR solutions only uses one pass to extract text information from an image, almost all modern OCR software uses two passes. This is especially true when using OCR on a handwritten document, since the software needs to build a baseline of what the handwriting looks like in comparison with the rules it already knows.
During the first scan, or first pass, the software only uses general information, like rules from feature detection or pattern recognition, to analyze the text in a document. It breaks down the characters into basic shapes so it can create a library of a given document’s font style or handwriting. This step is usually all that is necessary for typewritten text, but that is not always the case.
The second pass
During the second scan, or second pass, OCR software begins analyzing the symbols it recognizes and matching them to possible characters in its internal library. Since the OCR software already has some associations built between the characters in a document and the rules it already knows, this second scan can ensure higher accuracy in what it assumes each character to be.
What is OCR used for?
OCR is helpful in a number of use cases. It’s beneficial in any profession or industry that:
- Has workflows triggered by documentation
- Receives massive amounts of physical documentation that would otherwise need to be digitized manually
- Needs to have its documents digitized and searchable
OCR is even popular within consumer products. Many bank apps will allow customers to deposit checks from their phones via photograph. While users will usually also enter relevant information like the amount to be deposited, the confirmation process is often handled with OCR software.
Some real-time translation applications also rely on OCR if they’re translating text from photos. The application extracts the relevant text from the photograph or scanned area and then runs the extracted text through machine translation software to output translated text.
How do businesses benefit from OCR?
With all the possible uses for OCR, it’s unsurprising that OCR has become a staple in multiple industries such as accounting, health care, law and certain government bodies like post offices.
However, any business can benefit from having the ability to search, or CTRL/CMD+F, any relevant documentation.
While the process isn’t perfect and sometimes requires review before finalization, OCR technology is improving all the time. OCR software greatly reduces the time spent entering data and the rate of mistakes due to human error.
Looking for ways to automate your workplace? Check out our guide on office automation.