The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 29, 2018

Filed:

Nov. 06, 2015
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Sanjiv Kumar, White Plains, NY (US);

Henry Allan Rowley, Sunnyvale, CA (US);

Xiaohang Wang, Millburn, NJ (US);

Jose Jeronimo Moreira Rodrigues, Lisbon, PT;

Assignee:

GOOGLE LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G06K 9/18 (2006.01); G06K 9/66 (2006.01); G06T 3/00 (2006.01); G06K 9/00 (2006.01); G06Q 20/22 (2012.01); G06Q 20/34 (2012.01); G07F 7/08 (2006.01); G06K 9/32 (2006.01); G06K 9/46 (2006.01); G06T 7/11 (2017.01);
U.S. Cl.
CPC ...
G06K 9/6269 (2013.01); G06K 9/00469 (2013.01); G06K 9/00536 (2013.01); G06K 9/18 (2013.01); G06K 9/186 (2013.01); G06K 9/3233 (2013.01); G06K 9/3258 (2013.01); G06K 9/46 (2013.01); G06K 9/6202 (2013.01); G06K 9/6267 (2013.01); G06K 9/66 (2013.01); G06Q 20/227 (2013.01); G06Q 20/34 (2013.01); G06T 3/0012 (2013.01); G06T 7/11 (2017.01); G07F 7/0893 (2013.01); G06K 2009/4666 (2013.01); G06K 2209/01 (2013.01); G06T 2207/20132 (2013.01);
Abstract

Embodiments herein provide computer-implemented techniques for allowing a user computing device to extract financial card information using optical character recognition ('OCR'). Extracting financial card information may be improved by applying various classifiers and other transformations to the image data. For example, applying a linear classifier to the image to determine digit locations before applying the OCR algorithm allows the user computing device to use less processing capacity to extract accurate card data. The OCR application may train a classifier to use the wear patterns of a card to improve OCR algorithm performance. The OCR application may apply a linear classifier and then a nonlinear classifier to improve the performance and the accuracy of the OCR algorithm. The OCR application uses the known digit patterns used by typical credit and debit cards to improve the accuracy of the OCR algorithm.


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