US 12,307,814 B2
Material spectroscopy
Ali Hassani, Ann Arbor, MI (US); Jonathan Diedrich, Carleton, MI (US); Hamid M. Golgiri, Livonia, MI (US); Hemanth Yadav Aradhyula, Dearborn, MI (US); and John Robert Van Wiemeersch, Novi, MI (US)
Assigned to Ford Global Technologies, LLC, Dearborn, MI (US)
Filed by Ford Global Technologies, LLC, Dearborn, MI (US)
Filed on Nov. 10, 2023, as Appl. No. 18/506,317.
Application 18/506,317 is a division of application No. 17/147,832, filed on Jan. 13, 2021, abandoned.
Prior Publication US 2024/0087360 A1, Mar. 14, 2024
Int. Cl. G06V 40/16 (2022.01); G06T 5/40 (2006.01); G06T 7/11 (2017.01); H04N 23/11 (2023.01); B60R 25/25 (2013.01); B60R 25/30 (2013.01)
CPC G06V 40/171 (2022.01) [G06T 5/40 (2013.01); G06T 7/11 (2017.01); H04N 23/11 (2023.01); B60R 25/25 (2013.01); B60R 25/305 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/10048 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer, comprising:
a processor; and
a memory, the memory including instructions executable by the processor to:
acquire a first image by illuminating a first object with a first light beam;
segment the first image of the first object to determine first regions that correspond to a first surface material by inputting the first image to a convolutional neural network to determine first regions that include the first surface material and second regions that include non-first surface material;
determine a first measure of pixel values in the first regions of the first image that correspond to the first surface material;
perform a comparison of the first measure of pixel values to a second measure of pixel values determined from a second image of a second object, wherein the second image is previously acquired by illuminating the second object with a second light beam; and
when the comparison determines that the first measure is equal to the second measure of pixel values within a tolerance, determine that the first object and the second object are a same object.