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:
Feb. 24, 2015

Filed:

Dec. 17, 2013
Applicant:

Amazon Technologies, Inc., Reno, NV (US);

Inventors:

Oleg Rybakov, Seattle, WA (US);

Christopher John Lish, Seattle, WA (US);

Chang Yuan, Seattle, WA (US);

Junxiong Jia, Mercer Island, WA (US);

Rakesh Madhavan Nambiar, Seattle, WA (US);

Matias Omar Gregorio Benitez, Seattle, WA (US);

Assignee:

Amazon Technologies, Inc., Reno, NV (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06K 9/18 (2006.01); G06K 9/46 (2006.01); G06K 9/62 (2006.01); G06T 5/00 (2006.01);
U.S. Cl.
CPC ...
G06K 9/18 (2013.01); G06K 9/183 (2013.01); G06K 9/4604 (2013.01); G06K 9/6267 (2013.01); G06T 5/002 (2013.01);
Abstract

Embodiments of the subject technology provide methods and systems of image pre-processing for improving the accuracy of optical character recognition (OCR) and reducing the power consumption on a given computing device (e.g., mobile computing device). The subject technology, in some examples, classifies an image received from a camera of a mobile computing device into one or more classes: 1) normal background, 2) textured background, 3) image with text, 4) image with barcode, 5) image with QR code, and/or 6) image with clutter or 'garbage.' Based on the classes associated with the image, the subject technology may forgo certain image processing operations, when the image is not associated with a particular class, in order to save resources (e.g., CPU cycles, battery power, memory usage, etc.) on the mobile computing device.


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