Optical Character Recognition: What is OCR

optical character recognition

If you’ve ever travelled on a plane, written an email or even deposited cash at an ATM then you’ve made use of OCR technology. The optical character recognition is a procedure that computer software employed to convert text in an image or document in machine-readable language.

The most commonly used application for OCR technology is to extract handwritten or printed text from documents or shortly following the scanning process.

How does Optical Character Recognition work?

Optic character recognition software can be used for extracting text in an image. This is accomplished by the combination with computers with vision as well as pattern recognition in addition to artificial intelligence.

The procedure that is OCR is broken into five easy steps.

1. The process of scanning

The most important, and possibly most crucial aspect of the process, is beginning the process of scanning the documents. It is essential that the image that is created is exact depiction of the original without any imperfections that might hinder OCR. OCR process.

Documents should be scanned at the maximum resolution that is allowed and provide OCR software with the OCR application with the greatest chance of correctly in identifying the content.

The scanner should be calibrated against a test document and, when it comes to bulk scanning, calibrated several times during the process.

2. Image Processing

The following step then the optical character recognition software will then process the image that has been scanned to create the ideal circumstances for character recognition.

In the beginning, the program will fix any alignment issues that may have occurred during scanning and rotate the image until the document is correctly oriented.

Dust marks, stray marks and digital artifacts are removed , and the edges of objects are smoothed.

Then, the color information is eliminated then it is then possible to increase the brightness of the grayscale image increases to create the appearance of a highly contrasted images in black and white ( known by the term binarization). This creates a clearer distinction between the background ( that is the word ) and background, which reduces the possibility of misidentifying characters.

3. Character Recognition.

It’s in the process of character recognition that the optical character recognition software transforms the text within the document into its machine-language equivalent. The document is first examined for layout, and by identifying the location in text block and paragraphs. Then each area is broken down into words and lines.

In the end, each character is separated ( also known as “segmentation”) for translation. In the simplest OCR applications using pixel data in raw form, the data for every character is directly compared against a database of alphanumeric characters to determine the most closely-matched.

Advanced applications typically employ two different methods of optical character recognition:

  • Pattern Recognition: Pattern recognition works by looking at every character in its entirety and comparing it to the character matrix stored in the software. The disadvantage to this technique is it is based on input characters as well as the characters stored having the same size and shape.
  • Features extraction: Feature extraction provides a advanced and flexible method of recognition of characters that closely mimics the way that the human brain interprets text. The algorithm breaks down each character into its distinct characteristics, and identifies straight lines as well as curves, angles, angles and intersections. Then it matches the existence of these physical characteristics with the appropriate letter. The benefit of this method is that it doesn’t depend on a particular type of font to make recognition.

4. Verification

After each character is identified, the text is cross-referenced with the internal dictionary and lexicons that are known to increase the quality that the text will be produced.

Utilizing near-neighbor analyses, best OCR software looks for words and letters which are often paired and applies the “rules” to spot errors and then make corrections.

For instance, common digraphs (a combination of letters that represent the same sound in speech) comprising “qu”, “ea” and “ch” are easily rectified if a mistake is made in accordance with these guidelines.


In the process of converting image data to machine-coded text, scans become more useful, providing users of this digital format with capability to browse, view the contents, and even edit them.

This is why optical character recognition is now a common feature in both consumer and professional scanning software. It’s an essential feature for companies that deal with large volumes of documents that have been scanned.