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:
Jun. 10, 2025

Filed:

Dec. 02, 2020
Applicant:

Dolby Laboratories Licensing Corporation, San Francisco, CA (US);

Inventors:

Amirhossein Khalilian-Gourtani, New York, CA (US);

Neeraj J. Gadgil, Pune, IN;

Guan-Ming Su, Fremont, CA (US);

Assignee:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06V 10/762 (2022.01); G06F 18/23 (2023.01); G06F 18/23213 (2023.01); G06F 18/2323 (2023.01); G06F 18/40 (2023.01); G06T 5/30 (2006.01); G06T 7/11 (2017.01); G06T 7/155 (2017.01); G06T 7/90 (2017.01); G06V 10/26 (2022.01); G06V 10/28 (2022.01); G06V 10/34 (2022.01); G06V 10/44 (2022.01); G06V 10/56 (2022.01); G06V 10/764 (2022.01);
U.S. Cl.
CPC ...
G06V 10/7635 (2022.01); G06F 18/23 (2023.01); G06F 18/23213 (2023.01); G06F 18/2323 (2023.01); G06F 18/40 (2023.01); G06T 5/30 (2013.01); G06T 7/11 (2017.01); G06T 7/155 (2017.01); G06T 7/90 (2017.01); G06V 10/26 (2022.01); G06V 10/28 (2022.01); G06V 10/34 (2022.01); G06V 10/44 (2022.01); G06V 10/56 (2022.01); G06V 10/763 (2022.01); G06V 10/764 (2022.01); G06T 2200/24 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/20044 (2013.01); G06T 2207/20072 (2013.01);
Abstract

A method for image segmentation includes (a) clustering, based upon k-means clustering, pixels of an image into first clusters, (b) outputting a cluster map of the first clusters (c) re-clustering the pixels into a new plurality of non-disjoint pixel-clusters, and (d) classifying the non-disjoint pixel-clusters in categories, according to a user-indicated classification. Another method for image segmentation includes (a) forming a graph with each node of the graph corresponding to a first respective non-disjoint pixel-cluster of the image and connected to each terminal of the graph and to all other nodes corresponding to other respective non-disjoint pixel-clusters that, in the image, are within a neighborhood of the first respective non-disjoint pixel-cluster, (b) setting weights of connections of the graph according to a user-indicated classification in categories respectively associated with the terminals, and (c) segmenting the image into the categories by cutting the graph based upon the weights.


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