Granted Patent B2

US 12,602,769 · App. 17/410,193 · Granted Apr 14, 2026

Inventors: Adil Nizam Siddiqui (Farmington Hills, MI); Mahmoud Yousef Ghannam (Canton, MI); Jonathan Engels (Tecumseh, MI)

Assignee: Ford Global Technologies, LLC

G06T7/001G06T3/40G06T2207/10024G06T2207/30268

Abstract

Claims (56)

1 . A method for inspecting an interior of a vehicle, the method comprising:

performing a manufacturing routine to build a vehicle, wherein the manufacturing routine comprises a plurality of steps;

at each step of the plurality of steps, performing an inspection routine on an interior of the vehicle, wherein the inspection routine comprises:

obtaining image data from one or more imaging devices disposed in the interior of the vehicle, wherein the image data includes one or more images corresponding to the interior of the vehicle and a vehicle identification number;

generating, from averaging each pixel value of a first image of the image data with each pixel value of a second image of the image data, an averaged image;

modifying the averaged image based on a color conversion routine to generate a source image;

generating a conformity value based on a comparison between the source image and a template image corresponding to the interior of the vehicle, wherein the conformity value is a cross-correlation value, a normalized cross-correlation value, a sum-of-squared difference value, or a combination thereof;

determining a presence of a defect based on the conformity value;

identifying a component of the interior of the vehicle and pixel coordinates of the component based on a segmentation-based image processing routine; and

determining a type of the defect as an installation defect when the pixel coordinates of the component do not correspond to expected pixel coordinates of the component; and

remediating the installation defect in response to detecting the installation defect at one or more steps of the plurality of steps.

2 . The method of claim 1 , wherein modifying the image based on the color conversion routine to generate the source image further comprises converting the source image to one of a binary-type image and a grayscale-type image.

3 . The method of claim 1 further comprising adjusting an image scale of the template image in response to a size of the source image being unequal to a size of the template image.

4 . The method of claim 3 , wherein adjusting the image scale of the template image further comprises:

iteratively adjusting the image scale of the template image;

determining a correlation coefficient value for each iteration; and

determining a value of the image scale based on the correlation coefficient value of each iteration.

5 . The method of claim 1 , wherein modifying the averaged image further comprises:

converting the averaged image to a binary-type image.

6 . The method of claim 1 , wherein determining the presence of the defect further comprises comparing the conformity value to a reference conformity value.

7 . A system for inspecting an interior of a vehicle, the system comprising:

a processor; and

a non-transitory computer-readable medium comprising instructions that are executable by the processor, wherein the instructions comprise:

performing a manufacturing routine to build a vehicle, wherein the manufacturing routine comprises a plurality of steps;

at each step of the plurality of steps, performing an inspection routine on an interior of the vehicle, wherein the inspection routine comprises:

obtaining image data from one or more imaging devices disposed in the interior of the vehicle, wherein the image data includes one or more images and a vehicle identification number;

generating, from averaging each pixel value of a first image of the image data with each pixel value of a second image of the image data, an averaged image;

modifying the averaged image based on a color conversion routine to generate a source image, wherein the source image is one of a binary-type image and a grayscale-type image;

generating a conformity value based on a comparison between the source image and a template image corresponding to the interior of the vehicle, wherein the conformity value is a cross-correlation value, a normalized cross-correlation value, a sum-of-squared difference value, or a combination thereof;

determining a presence of a defect based on the conformity value;

identifying a component of the interior of the vehicle and pixel coordinates of the component based on a segmentation-based image processing routine; and

determining a type of the defect as an installation defect when the pixel coordinates of the component do not correspond to expected pixel coordinates of the component; and

remediating the installation defect in response to detecting the installation defect at one or more steps of the plurality of steps.

8 . The system of claim 7 , wherein the instructions further comprise adjusting an image scale of the template image in response to a size of the source image being unequal to a size of the template image.

9 . The system of claim 8 , wherein the instructions for adjusting the image scale of the template image further comprise:

iteratively adjusting the image scale of the template image;

determining a correlation coefficient value for each iteration; and

determining a value of the image scale based on the correlation coefficient value of each iteration.

10 . The system of claim 7 , wherein the instructions for determining the presence of the defect further comprise comparing the conformity value to a reference conformity value.

11 . A method for inspecting an interior of a vehicle, the method comprising:

performing a manufacturing routine to build a vehicle, wherein the manufacturing routine comprises a plurality of steps;

at each step of the plurality of steps, performing an inspection routine on an interior of the vehicle, wherein the inspection routine comprises:

obtaining image data from one or more imaging devices disposed in the interior of the vehicle, wherein the image data includes one or more images and a vehicle identification number;

generating, from averaging each pixel value of a first image of the image data with each pixel value of a second image of the image data, an averaged image;

modifying the averaged image based on a color conversion routine to generate a source image, wherein the source image is one of a binary-type image and a grayscale-type image;

generating a conformity value based on a comparison between the source image and a template image corresponding to the interior of the vehicle, wherein the conformity value is a cross-correlation value, a normalized cross-correlation value, a sum-of-squared difference value, or a combination thereof;

determining a presence of a defect based on the conformity value;

identifying a component of the interior of the vehicle and pixel coordinates of the component based on a segmentation-based image processing routine; and

determining a type of the defect as an installation defect when the pixel coordinates of the component do not correspond to expected pixel coordinates of the component; and

remediating the installation defect in response to detecting the installation defect at one or more steps of the plurality of steps.

12 . The method of claim 11 further comprising adjusting an image scale of the template image in response to a size of the source image being unequal to a size of the template image.

13 . The method of claim 12 , wherein adjusting the image scale of the template image further comprises:

iteratively adjusting the image scale of the template image;

determining a correlation coefficient value for each iteration; and

determining a value of the image scale based on the correlation coefficient value of each iteration.

14 . The method of claim 11 , determining the presence of the defect further comprises comparing the conformity value to a reference conformity value.

Assignments (1)

Continuity (1)

References Cited (28)