US 11,656,184 B2
Macro inspection systems, apparatus and methods
Matthew C. Putman, Brooklyn, NY (US); John B. Putman, Celebration, FL (US); John Moffitt, Los Banos, CA (US); Michael Moskie, San Jose, CA (US); Jeffrey Andresen, Gilroy, CA (US); Scott Pozzi-Loyola, Watsonville, CA (US); and Julie Orlando, Akron, OH (US)
Assigned to Nanotronics Imaging, Inc., Cuyahoga Falls, OH (US)
Filed by Nanotronics Imaging, Inc., Cuyahoga Falls, OH (US)
Filed on Aug. 5, 2022, as Appl. No. 17/817,826.
Application 17/817,826 is a continuation of application No. 17/170,467, filed on Feb. 8, 2021, granted, now 11,408,829.
Application 17/170,467 is a continuation of application No. 16/738,022, filed on Jan. 9, 2020, granted, now 10,914,686, issued on Feb. 9, 2021.
Application 16/738,022 is a continuation of application No. 16/262,017, filed on Jan. 30, 2019, granted, now 10,545,096, issued on Jan. 28, 2020.
Prior Publication US 2022/0383480 A1, Dec. 1, 2022
Int. Cl. G01N 21/88 (2006.01); G01N 21/00 (2006.01); G02B 21/26 (2006.01); G02B 21/36 (2006.01); G02B 21/06 (2006.01); G06V 20/69 (2022.01); G06V 10/774 (2022.01); G06T 7/00 (2017.01); H04N 5/235 (2006.01)
CPC G01N 21/8806 (2013.01) [G02B 21/06 (2013.01); G02B 21/26 (2013.01); G02B 21/365 (2013.01); G06T 7/0002 (2013.01); G06V 10/774 (2022.01); G06V 20/693 (2022.01); G06V 20/698 (2022.01); H04N 5/2354 (2013.01); G01N 2021/8835 (2013.01); G06T 2207/10056 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30024 (2013.01); G06T 2207/30148 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
generating, by a computing system, a training data set for training a prediction model to generate an illumination profile for a specimen positioned on a stage of an inspection apparatus, the training data comprising image data and non-image data of a plurality of training specimens;
training, by the computing system, the prediction model to generate illumination profiles for the plurality of training specimens, each illumination profile comprising one or more of an indication of lighting positions for a plurality of lights illuminating a corresponding specimen, an intensity level of each of the plurality of lights, a color of each of the plurality of lights, or distance information between each of the plurality of lights and the stage; and
applying, by the computing system, the prediction model to an image of the specimen to create the illumination profile for the specimen.