Developments in mobile network technology have facilitated numerous errands in our daily life, for example, shopping online and offline, paying utility bills, and transferring money. Such convenience is delivered by apps with the payment function that often requires a card to be bound to user's account. Users have to complete the whole binding process themselves, by manually inputting a long bank card number, which is both time-consuming and error-prone. The bank card recognition service from ML Kit overcomes these drawbacks by automatically recognizing a bank card's key details. With it, mobile apps can provide a better user experience and thus improve their competitiveness.
Service Introduction
The service leverages the optical character recognition (OCR) algorithm to recognize a bank card from the image or camera streams (whose angle offset can be up to 15 degrees) captured from a mobile device. Then the service can extract key card details like the card number, validity period, and issuing bank. Extracted details are then automatically recorded into the app. It works with the ID card recognition service to provide a host of handy functions including identity verification and card number input, simplifying the overall user experience.
Demo
Use Cases
Currently, binding bank cards is required by apps in a range of industries, including banking, mobile payment, and e-commerce. This service can accurately extract bank card details for the purpose of performing identity verification for financial services. Take an e-commerce app as an example. With the service integrated, such an app can record the bank card information that is quickly and accurately output by the service. In this way, the app lets users spend less time proving who they are and more time shopping.
Features
Wide coverage of bank cards: This service supports mainstream bank cards such as China UnionPay, American Express, Mastercard, Visa, and JCB, from around the world.
Accurate and fast recognition: The service recognizes a card in just 566 milliseconds on average, delivering a recognition accuracy of over 95% for key details.
How to Integrate ML Kit?
For guidance about ML Kit integration, please refer to its official document. Also welcome to the HUAWEI Developers website, where you can find other resources for reference.
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