Many apps require users to verify their identity in order to use their services offline (such as checking into a hotel) and online (booking a train/air ticket, playing a game, for example). This requires identity document details to be manually entered, which can sometimes be let down by typos.
With the ID Card Recognition feature from HMS Core ML Kit, entering incorrect details will be a thing of the past.
This feature leverages optical character recognition (OCR) technology to recognize formatted text and numbers of ID cards from images or camera streams. The service extracts key information (for example, name, gender, and card number) from the image of an ID card and then outputs the information in JSON format. This saves users from the trouble of manually entering such details, and significantly cuts the chances of errors occurring.
|ID Card||ID Number||Name||Gender||Validity Period||Birthday|
|Second-generation ID card of Chinese mainland residents||√||√||√||√||-|
|Vietnam ID card||√||√||√||-||√|
Apps in the mobile payment, traveling, accommodation, and other fields require an ID document image for identity verification purposes. This is where the ID Card Recognition service steps in, which recognizes and inputs formatted ID card information, for smooth, error-free input.
Take an e-commerce app for example. You can protect the security of your business by guaranteeing that all users shall verify their identity.
All-round card recognition: Recognizes all eight fields on the front and back of a second-generation ID card of Chinese mainland residents.
Fast recognition: Quickly recognizes an ID card in just 545.9 milliseconds.
High robustness: Highly adapts to environments where the lighting is poor or conditions are complex. In such environments, this service can still deliver a high recognition accuracy of up to 99.53% for major fields.
After integrating this service, my demo app received very positive feedback from its testers, regarding its fantastic user experience, high accuracy, and great efficiency.
I recommend you try out this service yourself and hope to hear your thoughts in the comments section.