Optical character recognition (OCR) software is crucial for any organization dealing in large-scale identity document scanning and processing. But what is OCR?
Whether referred to as a scanner or reader, OCR is an automated process that converts alphanumeric text from physical documents — captured by a digital image — into machine-readable text.
It may sound simple enough, but OCR is a diverse technology that can vary across industries and use cases. Commonly, it’s been used to convert dense text (e.g., legal or financial documents) into PDFs, which while voluminous, is a rather simple conversion process due to the uniform character recognition and structured formats traditionally involved with those files. And while modern OCR solutions are mostly software-based, there are still several examples of machine-based OCR (i.e., inline OCR) used in high-volume processing environments like mailrooms and product assembly lines.
All OCR solutions, however, are not created equal. For identity documents especially, a text recognition tool must be nimble due to the high degree of variance involved. IDs, whether passports, driver’s licenses, or national identity cards, are complex documents. Loaded with ever-evolving security features, watermarks, and signatures (not to mention varying design formats and language scripts), IDs are challenging enough to read — let alone accurately extract and reconstruct as machine-readable text.
Fortunately, the manual processes of ID data extraction and form filling, which tend to be riddled with errors and omitted information, have mostly gone away. While scanning has simplified the process for the end user, a poorly equipped OCR solution can cause friction by failing to read IDs from certain countries, or further struggling with out-dated formats and damaged documents. Not to mention, a lesser OCR scanner is more susceptible to the various forms of identity fraud.
For an OCR solution to truly stand out from the pack, it needs to thrive in any ID environment. Doing so not only allows an organization to save time and resources through reduced overhead, optimized data collection, and lower error rates, it also nets out a first-class, friction-free user experience across channels and devices.
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Optimize your customer experience with automated ID scanning
Microblink utilizes proprietary AI to transform standard OCR to intelligent image capture, making life simpler for hundreds of millions of users around the world. Microblink’s database of over 2,500 ID types (across 140 countries) illustrates the power and scale of AI-based document scanning — trained on constantly evolving machine learning models.
Our machine learning models are only as good as the data behind them. Microblink’s Data Annotation Platform (DAP) features configurable workflows for producing high-quality training datasets, enabling: easy management of projects/priorities, built-in quality monitoring tools, and support for large volumes of data.
What’s more, Microblink’s deep neural architectures come to life via our Machine Learning Platform (MLP), which lets our engineering team design, train, and evaluate the best models to be used in production.
Whether you need to onboard users to your platform or authenticate them at sign in, BlinkID is the world’s most trusted and flexible AI-enabled scanning solution. Our proprietary technology never stops growing and learning, supporting more than 2,500 ID types in 140 countries. Processing is done entirely on-device (with regional compliance regulations in mind), so information never has to leave your platform.
By delivering speed and accuracy at scale, BlinkID further delivers on the promise of unmatched user experience — guiding your most valuable stakeholders to a successful scan every time.
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