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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 11947631 B1

PDFFull Text
Date of Patent:
Apr. 02, 2024

Filed:

Sep. 22, 2021

Reverse image search based on deep neural network (dnn) model and image-feature detection model

Applicant:

Sony Group Corporation, Tokyo, JP;

Inventors:

Jong Hwa Lee, San Diego, CA (US);

Praggya Garg, Rancho Santa Fe, CA (US);

Assignee:

SONY GROUP CORPORATION, Tokyo, JP;

Attorney:

CHIP LAW GROUP

Primary Examiner:

Dhaval V Patel

Int. Cl.
CPC ...
G06K 9/00 (2022.01); G06F 3/14 (2006.01); G06F 18/22 (2023.01); G06F 18/2431 (2023.01); G06F 18/25 (2023.01); G06F 18/40 (2023.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); G06T 7/00 (2017.01); G06V 10/40 (2022.01); G06V 20/40 (2022.01);
U.S. Cl.
CPC ...
G06F 18/22 (2023.01); G06F 3/14 (2013.01); G06F 18/2431 (2023.01); G06F 18/253 (2023.01); G06F 18/40 (2023.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06T 7/0002 (2013.01); G06V 10/40 (2022.01); G06V 20/46 (2022.01); G06T 2207/10016 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30168 (2013.01);
Abstract

An electronic device and method for reverse image search is provided. The electronic device receives an image. The electronic device extracts, by a DNN model, a first set of image features associated with the image and generates a first feature vector based on the first set of image features. The electronic device extracts, by an image-feature detection model, a second set of image features associated with the image and generates a second feature vector based on the second set of image features. The electronic device generates a third feature vector based on combination of the first and second feature vectors. The electronic device determines a similarity metric between the third feature vector and a fourth feature vector of each of a set of pre-stored images and identifies a pre-stored image based on the similarity metric. The electronic device controls a display device to display information associated with the pre-stored image.

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