Improving user experience
for mobile device
card reading
Prepaid2cash (P2C) is a startup that for a small fee lets users cash in prepaid and gift cards. Users simply scan their cards and receive in their bank accounts the amounts.
CHALLENGE
P2C needed to be able to read both embossed and flat cards (cards with printed digits instead of embossed ones). They had identified an open source library that could be used to read embossed cards but that was failing to read flat ones.
P2C needed to be able to read both embossed and flat cards (cards with printed digits instead of embossed ones). They had identified an open source library that could be used to read embossed cards but that was failing to read flat ones.
SOLUTION
Working with our friends at DecemberLabs, a UX/UI and development company, our team built for P2C a custom component to perform the OCR in flat cards using deep learning models and image processing.
This solution is more flexible and accurate, it can read a much broader range of printed cards, and is faster than the pre-packaged version.
Working with our friends at DecemberLabs, a UX/UI and development company, our team built for P2C a custom component to perform the OCR in flat cards using deep learning models and image processing.
This solution is more flexible and accurate, it can read a much broader range of printed cards, and is faster than the pre-packaged version.
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