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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 11600003 B1

PDFFull Text
Date of Patent:
Mar. 07, 2023

Filed:

Sep. 25, 2020

Image processing apparatus and control method for an image processing apparatus that extract a region of interest based on a calculated confidence of unit regions and a modified reference value

Applicant:

Canon Kabushiki Kaisha, Tokyo, JP;

Inventor:

Takashi Sugimoto, Kawasaki, JP;

Assignee:

CANON KABUSHIKI KAISHA, Tokyo, JP;

Attorney:

Venable LLP

Primary Examiner:

Vu Le

Assistant Examiner:

Courtney Joan Nelson

Int. Cl.
CPC ...
G06T 7/11 (2017.01); G06T 7/62 (2017.01); G06T 7/50 (2017.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); G16H 50/50 (2018.01); G16H 50/30 (2018.01); G16H 50/20 (2018.01); G06N 3/04 (2006.01); G06F 3/04842 (2022.01); G06V 10/50 (2022.01); G06V 10/25 (2022.01);
U.S. Cl.
CPC ...
G06T 7/11 (2017.01); G06F 3/04842 (2013.01); G06N 3/04 (2013.01); G06T 7/50 (2017.01); G06T 7/62 (2017.01); G06V 10/25 (2022.01); G06V 10/50 (2022.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16H 50/50 (2018.01); G06T 2200/24 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20104 (2013.01); G06T 2207/30088 (2013.01); G06V 2201/03 (2022.01);
Abstract

An image processing apparatus includes an acquisition unit configured to acquire image data, a calculation unit configured to calculate, for each unit region of the image data, a confidence that the unit region is an extraction subject, the confidence as the extraction subject being calculated for each unit region of the image data by inputting the image data into a trained model of a neural network that has been trained using images of an existing extraction subject or a region of interest as training data, a modification unit configured to modify a reference value of the confidence, which is used to extract a region of interest, an extraction unit configured to extract the region of interest on the basis of the calculated confidence of each unit region and the modified reference value, and a display unit configured to display the extracted region of interest.

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