How Does Optical Character Recognition (Ocr) Work for Scanning Images or Texts?

Optical character recognition is the process of transforming an image of text into a text format that computers can read (OCR). For example, when you scan a receipt or a form, your computer saves the scan as an image file. It is impossible to edit, search, or count the words in an image file using a text editor. Optical character recognition software allows you to turn an image into a text document with its contents saved as text data.

Children and young people who have trouble reading can benefit greatly from these digital versions. Because of this, several readability-enhancing software programs can be used with digital text. Technology like an optical scanner or specialized circuit board is used to copy or read text, while software conducts any additional processing. OCR is mostly used to create PDF versions of hard-copy legal or historical documents. After the paper is saved in pdf format, users can edit, style, and analyze it as if it had been created using a word processor. Let’s discuss how optical character recognition (OCR) works for scanning images or texts.

How Does OCR Work?

Both hardware and software make up an OCR system. The service’s objective is to examine a physical document’s content and translate its components into a script that can then be used to handle data.

Think of postal and mail sorting services, for instance. OCR is essential to their ability to quickly process source and return addresses so that mail can be handled more effectively. The program’s three core techniques are as follows:

Processing Before Images

  • The method first changes the actual shape of the document into a picture, like a record picture. This stage’s goal is to make the machine’s representation accurate while eliminating any undesirable deviations.
  • The concept is then rendered in black and white and assessed for bright vs. dark sections (characters).
  • The image is then divided into distinct components, such as spreadsheets, text, or inset graphics, using an OCR system.

Character Recognition with AI

To identify characters and numbers, AI examines the dark areas of the image. One word, phrase, or paragraph at a time is typically the focus of one of the following strategies used by AI:

  • Pattern Recognition: Technologies train the AI system using a variety of languages, text types, and handwriting. To identify matches, the programmer compares the letters on the detected letter picture to the notes it has already learned.
  • Feature Recognition: To recognize new characters, the computer applies rules based on particular character traits. One example of a feature is the quantity of angled, intersecting, or curving lines in a letter.

The system applies criteria based on specific character traits to recognize original characters. One characteristic, for instance, is the quantity of angled, crossing, or bending lines in a character.


In the final file during post-processing, AI fixes errors. Educating the AI on a glossary of concepts that will occur in the paper is one strategy. Then, to make sure that no interpretations go outside the vocabulary, restrict the AI’s output to those words/formats.

Optical character recognition advantages

The three most significant advantages of OCR technology are time savings, a reduction in errors, and a decrease in the effort. The following options are not available with printed copies: zipping documents together, underlining words, integrating them into a website, and sending emails.

Final Words

Incorporating scanned documents into a big-data system that can now read customer information from contracts, bank statements, and other crucial printed documents is now possible thanks to OCR text recognition. Organizations can use Optical character recognition services to automate the input stage of data mining instead of requiring personnel to manually review numerous image documents and feed inputs into an automated big-data processing workflow. OCR software supports several file types, including jpg, jpeg, png, bmp, tiff, pdf, and others, and can recognize the text within an image, extract text from photos, and save the text file.