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The OCR challenge

An OCR engine is faced with a difficult task – deciphering information quickly and accurately, while confronted with any number of problems, including:

  • Font changes, unusual fonts and broken characters
  • Characters in different orientations on the page
  • Creased, crumpled, stained and smudged pages
  • Foreign language and character sets
  • Pages with text obscured by annotations and diagrams
  • Poor quality scanning devices, or ink on the scanner glass

At the end of all this, OCR programmes are expected to extract accurate information from documents – at speed. Naturally, many are unable to cope with the demands, and no OCR is genuinely 100% accurate.

How accurate is accurate?

Here's where the problem lies. Many OCR programs focus on speed – at the expense of truly accurate results. While they may claim high accuracy levels, when some engines are confronted with difficult tasks, such as the ones highlighted above, they give up (often after 30 seconds processing).

In many applications, the ability to extract meaningfuldata from the most difficult of documents is key to a project’s success – so you need an OCR engine that works harder to maximise the data it can extract.

Our solution

At Transym, we're confident that we have one of the most accountable forms of testing on the market. We've “taught” our software over a decade how to read and convert difficult information. TOCR draws on a database of tens of thousands of images, the result of near-constant research and improvement.

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