US 12,450,724 B2
Structural characteristic prediction for a honeycomb body using image abstraction
Jacob George, Horseheads, NY (US); Byoungseon Jeon, Malden, MA (US); Seth Thomas Nickerson, Corning, NY (US); and Hak Chuah Sim, Painted Post, NY (US)
Assigned to CORNING INCORPORATED, Corning, NY (US)
Appl. No. 18/020,826
Filed by CORNING INCORPORATED, Corning, NY (US)
PCT Filed Aug. 5, 2021, PCT No. PCT/US2021/044594
§ 371(c)(1), (2) Date Feb. 10, 2023,
PCT Pub. No. WO2022/035664, PCT Pub. Date Feb. 17, 2022.
Claims priority of provisional application 63/065,113, filed on Aug. 13, 2020.
Prior Publication US 2023/0334651 A1, Oct. 19, 2023
Int. Cl. G06T 7/00 (2017.01)
CPC G06T 7/001 (2013.01) [G06T 2207/20084 (2013.01); G06T 2207/30108 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method of inspecting a honeycomb body, comprising:
capturing a first image;
detecting one or more instances of at least one feature in the first image, the at least one feature correlating to a structural characteristic of the honeycomb body;
abstracting one or more detected instances of the at least one feature identified in the first image by creating a graphical representation of each of the one or more detected instances of the at least one feature;
generating a second image by augmenting the first image with the graphical representation in place of or in addition to each of the one or more detected instances of the at least one feature identified in the first image; and
analyzing the second image using a machine learning algorithm to classify the honeycomb body with respect to the structural characteristic of the honeycomb body.