What is OCR? How it is beneficial for businesses to avoid document fraud?

Optical Character Recognition (OCR) technology by recognize text from photo vector
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Since OCR stands for optical character recognition, it addresses the problem of recognizing a broad diversity of different characters. Both printed and handwritten characters can be recognized and converted into a machine-readable digital data format.

You can think of any serial number or code with numbers and letters that need to be digitalized. OCR can be used to translate these codes into a digital output. The technology makes use of several different techniques. Simply put, the characters are stripped from the processed image and then recognized.

OCR technology became more widespread throughout the early 1990s newspaper digitization process. Since then, technology has made significant progress. The OCR accuracy offered by modern solutions is almost flawless. Additionally, sophisticated methods like Zonal OCR are used to automate complicated document-based tasks.

OCR ignores the specific characteristics of the object you want to scan. It only “sees at” the characters that you want to translate into a digital format.

What is the Process of Optical Character Recognition?

Let’s examine the pre-processing of images, character recognition, and output post-processing—the three fundamental procedures of optical character recognition.

Image Pre-Processing in OCR

OCR software frequently does image pre-processing to improve the likelihood of successful recognition. The goal of picture pre-processing is to improve the image data itself. Unwanted distortions are lessened and some visual qualities are enhanced using this technique. These two procedures are necessary for the subsequent stages.

Character Recognition in OCR

To do the real character recognition, it is essential to understand “feature extraction”. When the input data is too large to process, just a reduced set of features is selected. The features that are chosen are assumed to be the most important, while the unimportant traits are ignored.

Post-Processing in OCR

Post-processing is another technique for error correction that ensures OCR’s high accuracy. The accuracy can be raised even further if the output is limited by a vocabulary. The algorithm can then, for instance, resort to a list of words that are allowed to exist on the scanned page.

OCR can recognize the right words in addition to reading codes and numbers. This allows for the identification of lengthy strings of numbers and letters, such as the serial numbers used in numerous industries.

To better handle a variety of input OCR formats, some service providers started developing distinctive OCR systems. These algorithms can handle distinctive images, and numerous optimization techniques have been included to further improve recognition accuracy.

For instance, they employed standardized language, business regulations, or detailed data present in the color image. “Application-oriented OCR” or “customized OCR” is the term used to describe this method of combining several optimization techniques. Applications utilizing it include ID card OCR, invoice OCR, and business card OCR.

What is OCR used for?

The most well-known application for OCR is the conversion of printed paper documents into text files that can be read by computers. After OCR processing, the text of a scanned paper document can be altered using word processors like:

  • Microsoft Word
  • Google Docs

The only method for digitizing printed paper documents before OCR solutions were invented was to manually retype the text. This required a lot of time, was wrong, and had typographical errors.

Numerous well-known systems and services that we use every day frequently use OCR as a “hidden” technology. OCR usage examples that are less well-known but nonetheless relevant include:

  • Airport passport recognition
  • Taking all details out of documents or business cards
  • Anti-bot CAPTCHA methods defeated
  • Making electronic documents recognizable like Google Books or PDFs
  • Data entry for business documents

Old newspapers and other materials have been converted into fully searchable copies thanks in large part to OCR technology, which has made it much quicker and simpler to locate those earlier texts.

Kevin Peter