Optical Character Recognition – Short Explanation

Optical Character Recognition or OCR is a technology that has been around for many years, but due to some recent improvements, it is now much more capable. OCR is the process of scanning or converting handwritten or typed text and converting that information into a format that can be manipulated on and by machines. OCR can be used to convert almost any image that includes text into data that can be manipulated, edited, and used.

Historically OCR has been used as a means of digitizing old papers and newspapers that had been created and published prior to the advent of technology. This process not only simplifies storage, but it also helps make the information available to everyone. Early iterations of OCR required significant intervention and analysis to isolate and authenticate the images scanned manually. In addition, previous generations of OCR were limited in the number and types of font faces that were “understood” by the software.

Optical Character Recognition in the Real World

To understand how OCR works, consider a printed document with names, addresses, and other useful information like courses taken and grades received. To manipulate this data and find out specific information, the information needs to be in a format that can be accessed on a PC.

Through the use of OCR, images are processed in a variety of different ways to boost opportunities for character recognition. These techniques include:

  • De-skewing – documents scanned are not always correctly aligned. The software is able to correct for this discrepancy by adjusting the image.
  • Despeckle – OCR software can remove positive and negative spots from images and also smooth the edges to make the text more recognizable.
  • Binarization – by converting images into black-and-white, text is more easily discovered.
  • Line removal and layout analysis – OCR software is able to identify columns, lines, and paragraphs as blocks. This helps to ensure text can be manipulated more easily.
  • Script and word recognition – with documents that have multiple languages present, the software needs to understand the differences and correctly analyze and divide words.
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Optical Character Recognition in the World of AI

OCR is being revolutionized through the use of AI. Now, data is not only captured and analyzed, but based on the information obtained, appropriate action is taken. Some examples of the combination of OCR and AI include a streamlining of the invoicing process for organizations based on scanned data. In a similar vein, OCR and AI can be used to verify expense management by ensuring related entries are automatically flagged.