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OCR Studio updates AI MRZ scanning for difficult remote ID captures

On-device AI extracts passport and ID data from blurred, angled and low-quality images
OCR Studio updates AI MRZ scanning for difficult remote ID captures
 

OCR Studio has updated its on-device software to scan the machine readable zones (MRZs) of passports, identity cards, visas, and other documents captured during remote onboarding.

The company says its AI-enabled OCR MRZ scan technology can extract identity and document information from low-resolution images and documents photographed at difficult angles or under conditions involving shadows and blur.

The update is designed to improve first-pass document capture, reducing repeated scans and manual reviews during remote identity verification.

OCR Studio targets banks, fintech companies and retailers that verify identity documents captured on customer-operated devices.

Remote identity verification shifts the capture process to customers, who often use personal phones and webcams under varying image processing software and operating conditions.

In some instances, a document may be worn or poorly illuminated, while the user may hold it at an angle or move the camera during capture.

Those conditions often prevent software from reliably locating and reading the machine readable zone (MRZ). The commercial challenge is achieving accurate first-pass extraction across different document types, devices and lighting conditions.

Recognition occurs locally within mobile apps and web browsers, allowing document data to be extracted without sending images to the cloud. However, on-device processing alone does not determine privacy compliance. Organizations deploying the software may still transmit, store or process document images and extracted data as part of their identity verification workflows

Demand for reliable document capture extends beyond commercial onboarding. U.S. Citizenship and Immigration Services recently requested remote identity verification technology that could operate across major phones and browsers through image capture and identify quality problems.

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