Extracting card data using IIN database

• US 9,292,740 B2
• Filed: 12/03/2014
• Issued: 03/22/2016
• Est. Priority Date: 06/28/2013
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Kumar, Sanjiv, Wang, Xiaohang, Rodrigues, Jose Moreira, Shamsi, Farhan, Okshtein, Yakov, Rowley, Henry Allan, Mitchell, Marcus Quintana, Li, Zhifei
• Primary Examiner(s): VO, TUYEN KIM
• Application Number:
  US14/559,888
• Publication Number:
  US 20150086069A1
• Time in Patent Office: 475 Days
• Field of Search: 235/375, 235/449, 235/493, 235380-383, 235/451, 235/472.01, 235/492
• US Class Current: 1/1
• CPC Class Codes: G06K 7/10 by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
• CPC Class Codes: G06Q 20/3223 Realising banking transactions through M-devices
• CPC Class Codes: G06Q 20/326 Payment applications installed on the mobile devices
• CPC Class Codes: G06Q 20/3276 using a pictured code, e.g. barcode or QR-code, being read by the M-device
• CPC Class Codes: G06Q 20/34 using cards, e.g. integrated circuit [IC] cards or magnetic cards
• CPC Class Codes: G06Q 20/36 using electronic wallets or electronic money safes
• CPC Class Codes: G06V 30/10 Character recognition
• CPC Class Codes: G06V 30/142 using hand-held instruments; Constructional details of the instruments
• CPC Class Codes: G06V 30/224 of printed characters having additional code marks or containing code marks
• CPC Class Codes: G06V 30/2253 Recognition of characters printed with magnetic ink G06V30/2247 takes precedence
• CPC Class Codes: G06V 30/416 Extracting the logical structure, e.g. chapters, sections or page numbers; Identifying elements of the document, e.g. authors
• CPC Class Codes: H04N 1/00307 with a mobile telephone apparatus constructional features of portable telephone sets H04M1/0202; mobile radio systems H04W84/00

Abstract

Extracting card data comprises receiving, by one or more computing devices, a digital image of a card; perform an image recognition process on the digital representation of the card; identifying an image in the digital representation of the card; comparing the identified image to an image database comprising a plurality of images and determining that the identified image matches a stored image in the image database; determining a card type associated with the stored image and associating the card type with the card based on the determination that the identified image matches the stored image; and performing a particular optical character recognition algorithm on the digital representation of the card, the particular optical character recognition algorithm being based on the determined card type. Another example uses an issuer identification number to improve data extraction. Another example compares extracted data with user data to improve accuracy.

Claims

1. A computer-implemented method for extracting financial card information, comprising:

determining, by the one or more computing devices, a first location on an image of a financial card of an identification number associated with the financial card;

perform, by the one or more computing devices, a first optical character recognition algorithm on the first location on the digital image;

identifying, by the one or more computing devices, an identification number associated with the financial card from information obtained from application of the first optical character recognition algorithm to the first location on the digital image;

comparing, by the one or more computing devices, the identification number to a database of identification numbers and card types;

determining, by the one or more computing devices, a card type associated with the financial card;

selecting, by the one or more computing devices, a second optical character recognition algorithm tailored to predicted features of the card based on the determination of the card type; and

performing, by the one or more computing devices, the second optical character recognition algorithm on the digital image to extract information from the digital image of the financial card.

2. The method of claim 1, wherein the second optical character recognition algorithm comprises a particular set of constraints related to the card type.

3. The method of claim 2, wherein the set of constraints comprises information locations on the card image.

4. The method of claim 2, wherein the set of constraints comprises a list of categories of information represented on the card.

5. The method of claim 1, wherein the card comprises one or more of a credit card, a debit card, an identification card, a loyalty card, an access card, or a stored value card.

6. The method of claim 1, wherein the database is an issuer identification number database.

7. The method of claim 1, wherein the database of identification numbers is selected for comparison based on user data stored by the one or more computing devices.

8. A computer program product, comprising:

a non-transitory computer-readable storage device having computer-executable program instructions embodied thereon that when executed by a computer cause the computer to extract financial card information, comprising;

computer-readable program instructions to determine a first location on an image of a financial card of an identification number associated with the financial card;

computer-readable program instructions to perform a first optical character recognition algorithm to the first location on the digital image;

computer-readable program instructions to identify an identification number associated with the financial card from information obtained from application of the first optical character recognition algorithm to the first location on the digital image;

computer-readable program instructions to compare the identification number to a database of identification numbers and card types;

computer-readable program instructions to determine a card type associated with the financial card;

computer-readable program instructions to select a second optical character recognition algorithm tailored to predicted features of the card based on the determination of the card type; and

computer-readable program instructions to perform the second optical character recognition algorithm to on the digital image to extract information from the digital image of the financial card.

9. The computer program product of claim 8, wherein the second optical character recognition algorithm comprises a particular set of constraints related to the card type.

10. The computer program product of claim 9, wherein the set of constraints comprises information locations on the card image.

11. The computer program product of claim 9, wherein the set of constraints comprises a list of categories of information represented on the card.

12. The computer program product of claim 8, wherein the card comprises one or more of a credit card, a debit card, an identification card, a loyalty card, an access card, or a stored value card.

13. The computer program product of claim 8, wherein the database is an issuer identification number database.

14. The computer program product of claim 8, wherein the database of identification numbers is selected for comparison based on user data stored by the one or more computing devices.

15. A system to extract financial card information, the system comprising:

a storage resource;

a processor communicatively coupled to the storage resource, wherein the processor is configured to execute computer-readable instructions that are stored in the storage resource and that cause the system to;

determine a first location on an image of a financial card of an identification number associated with the financial card;

perform a first optical character recognition algorithm to the first location on the digital image;

identify an identification number associated with the financial card from information obtained from application of the first optical character recognition algorithm to the first location on the digital image;

compare the identification number to a database of identification numbers and card types;

determine a card type associated with the financial card;

select a second optical character recognition algorithm tailored to predicted features of the card based on the determination of the card type; and

perform the second optical character recognition algorithm to on the digital image to extract information from the digital image of the financial card.

16. The system of claim 15, wherein the second optical character recognition algorithm comprises a particular set of constraints related to the card type.

17. The system of claim 16, wherein the set of constraints comprises information locations on the card image.

18. The system of claim 16, wherein the set of constraints comprises a list of categories of information represented on the card.

19. The system of claim 15, wherein the card comprises one or more of a credit card, a debit card, an identification card, a loyalty card, an access card, or a stored value card.