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What is optical character recognition (OCR) technology?

The demand for accurate business data on demand only grows each day. OCR technology gets mission-critical information to your team without slowing down workflows.

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What is OCR?

Optical character recognition (OCR) technology is a business solution for automating data extraction from printed or written text from a scanned document or image file and then converting the text into a machine-readable form to be used for data processing like editing or searching.

How does OCR work?

OCR software applications might operate slightly differently, but they do adhere to a few universal rules. OCR technology commonly works through a step-by-step process of:

1. Image acquisition

A scanner reads physical paper documents and converts them into a scanned image. The file is commonly rendered in black and white, which will then be used to differentiate the brighter (background) and darker (characters) regions from each other.

2. Pre-processing

Here, the OCR engine corrects errors through methods like de-skewing, binarization, zoning and normalization to improve the accuracy of scanned images.

3. Text recognition

Artificial intelligence (AI) tools can be used here to identify original characters from a scanned image or document. This can be done through two main algorithms, pattern matching and feature extraction.

4. Post-processing

The OCR software then converts the extracted data into electronic documents. Advanced OCR systems can compare extracted data against a glossary or library of characters to ensure maximum accuracy.

What are the different types of OCR technologies?

The various types of OCR technologies can be categorized based on what they can capture. These include:

  • Optical Character Recognition (OCR). OCR systems recognize handwritten or typed characters based on an existing internal database.
  • OWR Word Recognition (OWR). OWR is usually just referred to as OCR. This method targets typewritten text, one specific word at a time, and is used for languages that divide words with spacing.
  • Optical Mark Recognition (OMR). The OMR type analyzes watermarks, logos, symbols, marks and patterns on a paper document.
  • Intelligent Character Recognition (ICR). ICR uses data capture tools to read text handwritten or cursive text. This method uses machine learning and AI technology to analyze the different elements of the text (curves, loops, lines, etc.). ICR identifies and processes a single character at a time.

What is Optical Character Recognition (OCR) used for?

Almost any type of image containing written text (typed, handwritten, or printed) can be transformed into machine-readable text data using OCR technology. The data can then be used to streamline operations, automate procedures and boost efficiency.

Organizations can leverage OCR tools to improve:

  • Accounts payable (AP) and invoicing
  • Claims processing
  • Patient form submission
  • Automated transcript data capture
  • Loan verification

Benefits of automated OCR technology

Businesses that employ OCR capabilities to convert images and PDFs (typically originating as scanned paper documents) save time and resources that would otherwise be necessary to manage unsearchable data. Once transferred, OCR-processed textual information can be used by businesses more quickly and easily.

The benefits of OCR technology to businesses include:

Improved information accessibility

OCR adds the functionality of editing and searching materials from a digital archive. OCR-processed digital files, (such as receipts, contracts, invoices, financial statements, etc.) can be:

  • Searched from a large repository to find the correct document
  • Viewed, with search capability within each document
  • Edited, when corrections need to be made
  • Repurposed, with extracted text sent to other systems

Reinforced data security

Security is a major concern for all companies that handle the digital data of their customers. OCR technology provides an extra layer of security when processing and extracting information. The banking sector, for instance, can digitize paperwork with greater accuracy through OCR. OCR ensures that data extraction and verification can happen faster, minimizing the risks of fraud, identity theft or manual errors.

Increased operational efficiency

Accessing, sharing and storing physical documents will lead to costly bottlenecks. Businesses can utilize OCR software to go paperless and automate mission-critical workflows daily. The right data capture system will allow your teams to automatically extract, validate and classify data in much less time than they could manually.


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The value and breadth of data classification and capture solutions

OCR, the ability to extract machine-printed text from a digital image, is only one aspect of a data capture solution. Data can be extracted from documents in many different formats — hand printed text (ICR), check boxes (OMR), bar codes, etc.

Robust data capture solutions handle multiple document formats and can be used with both electronic and paper documents, eliminating paper and reducing manual identification and data entry of document content into other systems.

By employing an OCR system within a data capture solution, businesses can:

  • Reduce costs
  • Accelerate processes
  • Automate document routing and content processing
  • Centralize and secure data (no fires, break-ins or documents lost in the back vaults)
  • Improve service by ensuring employees have the most up-to-date, accurate information when they need it

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