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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 12682449 B1

PDFFull Text
Date of Patent:
Jul. 14, 2026

Filed:

Oct. 28, 2024

Automated defect recognition and determinations of pore cluster compliance

Applicant:

Relativity Space, Inc., Long Beach, CA (US);

Inventors:

Christopher Sacco, Long Beach, CA (US);

Viraj Sinha, Long Beach, CA (US);

Kyle Buzza, Long Beach, CA (US);

Salik Syed, Long Beach, CA (US);

Andrew Taormina, Long Beach, CA (US);

Bryson Jones, Long Beach, CA (US);

Cem Tutum, Long Beach, CA (US);

Jeffrey Rossin, Long Beach, CA (US);

Assignee:

Relativity Space, Inc., Long Beach, CA (US);

Attorney:

KPPB LLP

Primary Examiner:

David F Dunphy

Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06T 7/11 (2017.01); G06T 7/62 (2017.01); G06T 7/64 (2017.01); G06V 10/26 (2022.01); G06V 10/32 (2022.01); G06V 10/762 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06T 7/001 (2013.01); G06T 7/11 (2017.01); G06T 7/62 (2017.01); G06T 7/64 (2017.01); G06V 10/26 (2022.01); G06V 10/32 (2022.01); G06V 10/762 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06T 2207/10116 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20092 (2013.01); G06T 2207/30136 (2013.01);
Abstract

A process can obtain a RT image of an article from the RT imaging system, the article comprising a reference feature, identify a first portion and a second portion of the first RT image, wherein the first portion and the second portion overlap, and classify each pixel in the first portion and the second portion using a pore classification model. A pore map can then be generated and mapped onto the article based on data received from the at least one sensor. A process can identify rejected regions on the pore map, wherein the rejected regions exceed a rejection threshold based on predefined rules. These rejected regions can then be displayed.

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