| 摘要 |
Financial transaction card data can be entered by providing a picture of the card to a server programmed with a text recognition algorithm. The server can perform text recognition on the image at the same time that a consumer enters additional required data, such as a zip code. The server can perform as much text recognition processing as possible in the time the consumer is entering the additional data. Once the additional data is received, a signal can be provided to the server indicating that the user is now waiting for results of the text recognition process, meaning the server should provide them as quickly as possible. Once text recognition results are received, a consumer can make a selection to identify a character which the text recognition algorithm did not sufficiently identify. Based on known account number constraints, the user selection can cause multiple characters to be identified. |
| 主权项 |
1. A method, performed on a mobile computing device, for reducing a number of user corrections entered to obtain a correct account number for a financial transaction card, the method comprising: obtaining, at the mobile computing device, multiple versions of text recognition results, wherein each version of the text recognition results is associated with a total confidence score; identifying, as a best guess, a version of the text recognition results that is associated with a highest total confidence score; selecting, based on individual confidence scores of characters of the best guess, characters to verify from the best guess; receiving a user selection, as a selected character, for one of the characters to verify; and updating the multiple versions of the text recognition results by performing one or more of: eliminating, from the multiple versions of text recognition results, one or more of the multiple versions of text recognition results that do not match the selected character; eliminating, from the multiple versions of text recognition results, one or more of the multiple versions of text recognition results that do not satisfy the Luhn algorithm; eliminating, from the multiple versions of text recognition results, one or more of the multiple versions of text recognition results that do not match any of multiple known issuer identification numbers; updating the total confidence score for the multiple versions of text recognition results; or any combination thereof; and identifying a new best guess from the remaining versions of the text recognition results, wherein the new best guess comprises at least a first difference from the best guess that is a change of a first character in the best guess to the selected character, and a second difference from the best guess that is a change of a second character in the best guess other than to the selected character. |
