OCR (Optical Character Recognition) – what is it?
OCR (Optical Character Recognition) It is a technology that converts text found in an image—such as a scan, a photo, or a PDF file—into digital text that a computer can read. To a human, a scanned invoice looks like a document with text, but to a computer, it is just a collection of pixels. OCR extracts letters and numbers from it, making the content searchable, copyable, editable, and automatically processable.
In practice, OCR eliminates the need to manually transcribe data from paper documents and scans. Information that used to have to be entered manually is automatically fed into the system.
How does OCR work?
Text recognition takes place in several steps. First, the program prepares the image: it straightens skewed pages, removes smudges, adjusts the contrast, and sharpens the text. Next, it determines the document’s layout—that is, where blocks of text, tables, and images are located—and finally, it recognizes individual characters and assembles them into words. In the past, this was done by comparing the shapes of letters to templates; today, neural networks are primarily used, as they handle different fonts and lower-quality images more effectively. In the final phase, the result is corrected based on dictionaries and rules—for example, rules that detect that an account number should not contain letters.
The result is usually text along with information about its location on the page. Often, a PDF document with a text layer is also created, which looks like the original but allows users to search for and highlight words.
Applications of OCR in the company
OCR is useful wherever a company receives documents in paper form or as scans. It is most commonly used to:
- extract data from invoices, such as the number, date, amount, tax ID, and name of the business partner,
- log incoming correspondence and automatically tag documents,
- digitizing archives so that documents can be searched by content,
- processing contracts and other documents where specific information needs to be found,
- reading identification documents and forms filled out on paper.
In document workflow systems, OCR is usually the first step in the process: the extracted data is entered into a form, and the document is sent for approval without the need for manual data entry.
What determines the quality of character recognition?
The effectiveness of OCR depends primarily on the quality of the source. A sharp, well-lit scan with adequate resolution yields significantly better results than a blurry photo taken with a cell phone. The font, document layout, and language also matter—particularly diacritical marks in the case of Polish. Handwriting is more difficult to recognize than printed text. Since even a good solution can make mistakes, it’s worth ensuring that results are checked by a human or validated automatically when dealing with important data, such as amounts or account numbers.
OCR and Related Concepts
Scanning documents merely creates an image of the page. Only OCR extracts text from that image, so while the two steps complement each other, they are not the same. ICR (Intelligent Character Recognition) is an advancement of OCR designed to recognize handwriting.
AI OCR, or intelligent document processing, goes a step further: it not only reads the text but also understands what it means. It recognizes that a given number is a gross amount and that a string of characters is an invoice number, even when documents vary in layout. This makes it possible to process documents with variable structures without creating a separate template for each business partner.