How to use Optical Character Recognition technology

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When it comes to data extraction and digitising real-world documentation or imagery on your desktop computer, there is a much easier and quicker way than using an old-school scanner. Optical Character Recognition (OCR) technology has rapidly proven to be an effective B2B and B2C solution for converting data into a machine-readable format.

This is particularly beneficial for those who want to create substantial repositories of files including expenses receipts, contracts, bank statements, employee data and much more. The beauty of OCR is that scanned data can be digitised and made fully editable, which is ideal for when revisions need to be made. Furthermore, these edited and repurposed digital files can also be extracted and distributed to other internal systems. This proves particularly popular for when devices and systems won’t boot.

OCR has transformed the vehicle industry, with its ability to power automatic number plate recognition (ANPR) technology suitable for car parking and monitoring vehicles being driven without valid MOTs, tax or insurance. With OCR a popular solution for creating repositories, it’s also been useful in the indexation of real-world documentation for leading search engines like Google.

OCR solutions have also proven particularly effective in the iGaming industry, where OCR cameras are used in live casino studios to provide rapid conversion of card-based gaming data to be overlaid on-screen in real time. This has proven particularly popular with real money versions of classic table games like blackjack, helping to facilitate the natural flow of the 52-card game.

How does OCR technology work?

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Let’s say that you have a scan of a new employee’s contract on your system. By capturing it using OCR technology it’s possible to make the contract simultaneously searchable and editable. Old-school scanners don’t make it possible to edit the data hard copy scanned. All it is programmed to do is take a snapshot of the raw data in what’s known in the industry as a ‘raster image’.

Whether it’s an image-only PDF, a scanned document or an image from a camera or smartphone, OCR technology can locate and convert content or letters from scanned documents or images and translate them into digitised words and sentences. The end result is the entire document becomes a fully editable, digital form.

Getting to grips with OCR software

There are multiple OCR software solutions out there, but here are a few providers that we’d recommend to get you started on your journey to machine-readable data processing:

  • ABBYY FineReader

    ABBYY’s FineReader solution is underpinned by its Artificial Intelligence-powered OCR technology, designed to “maximise efficiency in the digital workplace”. ABBYY has been in the OCR marketplace for almost three decades, boasting a corporate client base of approximately 17,000 users and installed on over 100 million commercial and residential devices worldwide. Whether you need it for B2C or B2B purposes, FineReader makes it easier to bring physical documentation and content into digital workflows, therefore making it easier to collaborate, convert, edit, share and protect in the digital world.


  • Hyland OnBase

    Hyland fully understands that we live in an Information Age. Its Experience Capture solution makes it possible to leverage OCR technology and capture data and content anywhere. Hyland Experience Capture (HxC) is a web-based service offering data extraction, document scanning and classification via the cloud. OCR is fused with machine learning to improve the overall accuracy of its data capture. As a cloud-based solution, it offers an almost zero carbon footprint and simple deployment across all manner of departments.


  • Docparser

    Docparser is another highly agile OCR solution that can pinpoint and extract data from image-based documents, as well as PDFs and Word documents via Zonal OCR technology. It also relies on advanced pattern recognition powered by AI. It uses a three-step process for parsing documents. Documents are uploaded to the cloud. Users set the rules Docparser needs to fit the document type and the digitised format is then downloadable via multiple formats.

The digitisation of real-world data has never been so seamlessly collected thanks to OCR technology’s human-like intelligence.

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