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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.

Patent No.:

US 11847661 B1

PDFFull Text
Date of Patent:
Dec. 19, 2023

Filed:

Nov. 15, 2018

Image based counterfeit detection

Applicant:

3m Innovative Properties Company, St. Paul, MN (US);

Inventors:

Nicholas A. Asendorf, St. Paul, MN (US);

Jennifer F. Schumacher, Woodbury, MN (US);

Robert D. Lorentz, North Oaks, MN (US);

James B. Snyder, Minneapolis, MN (US);

Golshan Golnari, Maple Grove, MN (US);

Muhammad Jamal Afridi, Woodbury, MN (US);

Assignee:

3M Innovative Properties Company, St. Paul, MN (US);

Attorneys:

Sriram Srinivasan

Yufeng Dong

Primary Examiner:

Leon Viet Q Nguyen

Int. Cl.
CPC ...
G06Q 30/00 (2023.01); G06Q 30/018 (2023.01); G06T 7/73 (2017.01); G06F 16/55 (2019.01); G06F 16/53 (2019.01); G06N 20/00 (2019.01); G06F 16/56 (2019.01); G06N 5/04 (2023.01); G06T 7/00 (2017.01); G06F 18/24 (2023.01); G06F 18/214 (2023.01); G06V 10/764 (2022.01); G06V 10/44 (2022.01); G06V 10/50 (2022.01); G06V 10/46 (2022.01);
U.S. Cl.
CPC ...
G06Q 30/0185 (2013.01); G06F 16/53 (2019.01); G06F 16/55 (2019.01); G06F 16/56 (2019.01); G06F 18/214 (2023.01); G06F 18/24 (2023.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06T 7/0004 (2013.01); G06T 7/73 (2017.01); G06V 10/449 (2022.01); G06V 10/50 (2022.01); G06V 10/764 (2022.01); G06T 2200/24 (2013.01); G06T 2207/30108 (2013.01); G06V 10/467 (2022.01);
Abstract

Systems and methods for authenticating material samples are provided. Digital images of the samples are processed to extract computer-vision features, which are used to train a classification algorithm along with location and optional time information. The extracted features/information of a test sample are evaluated by the trained classification algorithm to identify the test sample. The results of the evaluation are used to track and locate counterfeits or authentic products.

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