Optical Character Recognition Services and techniques

October 28, 2020

Many businesses are facing trouble carrying out their data entry operations. Manually entering data is a hectic task. Data managed manually not only wastes a lot of time but it also provides no surety of data security. Humans are prone to errors so entering data manually can also be inaccurate. OCR- Optical Character Recognition is a data extraction technology that answers the data entry operation. In this blog, we will talk about how optical character recognition technology has benefitted businesses. 

What is Optical Character Recognition?

OCR technology was originally designed to extract data from its image form and display it in its online form. The conventional OCR engine works by analyzing the patterns and images. The text is extracted in a form that can be understood by the machine. Then this extracted document is turned into a digital form that can be edited. OCR technology can be used to scan and extract information on documents like ID cards, driver’s licenses, utility bills, invoices, recipes, contracts, passports, etc. 

This OCR technology has its advantages but it also has its faults. It might help the companies with their data entry operations but it is still not that accurate. Hence the issue still exists that requires human supervision to correct the errors and the time is still wasted. However, to meet the demands of the fast-paced world, artificial intelligence is integrated with optical character recognition technology to provide an intelligent solution to this problem.

AI-based Optical Character Recognition 

Artificial intelligence uses a machine-learning algorithm to extract data online. Computer vision can extract data in its image form and provides more accurate result. The language processing algorithm can extract data in multi-languages. Intelligent OCR can understand the type of document, its format, and other tiny details. It also has a detailed comprehension of the data written on the document. The AI-based OCR solution provides a higher accuracy rate than the traditional OCR engine. 

  1. Pre-processing

The pre-processing occurs using various features. Here is a list of these features.

  • De-Skew and Despeckle 

De-Skew is used to give the extracted document a proper alignment. Data must be extracted properly without any spots or folded edges. Despeckle can correct the edges and removes the smudges so the document is properly extracted. 

  • Binarisation

When colored images are turned into a binary image, its called Binarisation. The OCR process works on binary images so this process is necessary.

  • Layout and line removal

Columns and paragraphs are identified through this feature. It filters out the lines and boxes and non-glyphs. If data is written in the column form, these features can help in thorough data extraction.

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