Vehicle image sensor cleaning

• US 10,518,751 B2
• Filed: 09/18/2017
• Issued: 12/31/2019
• Est. Priority Date: 09/18/2017
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Seubert, Christopher Michael, Nichols, Mark Edward, Peters, Cindy Anne, Holguin, Kerrie Nikaido
• Primary Examiner(s): Golightly, Eric W
• Application Number:
  US15/708,015
• Publication Number:
  US 20190084526A1
• Time in Patent Office: 834 Days
• Field of Search: None
• CPC Class Codes: B60R 11/04 Mounting of cameras operative during drive; Arrangement of controls thereof relative to the vehicle
• CPC Class Codes: B60R 2011/004 outside the vehicle
• CPC Class Codes: B60S 1/04 Wipers or the like, e.g. scrapers
• CPC Class Codes: B60S 1/0822 characterized by the arrangement or type of detection means
• CPC Class Codes: B60S 1/56 specially adapted for cleaning other parts or devices than front windows or windscreens rear-view mirror arrangements mounted on vehicle exterior including cleaning devices B60R1/0602
• CPC Class Codes: G06T 2207/10004 Still image; Photographic image
• CPC Class Codes: G06T 2207/20132 Image cropping
• CPC Class Codes: G06T 2207/30248 Vehicle exterior or interior
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 5/00 Image enhancement or restoration
• CPC Class Codes: G06T 5/90 Dynamic range modification of images or parts thereof
• CPC Class Codes: G06T 7/001 using an image reference approach
• CPC Class Codes: G06T 7/74 involving reference images or patches
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: H04N 23/811 by dust removal, e.g. from surfaces of the image sensor or processing of the image signal output by the electronic image sensor

Abstract

A vehicle computer includes a memory and a processor programmed to execute instructions stored in the memory. The instructions include comparing a captured image of a predetermined object to a target image of the predetermined object to quantify a first noise characteristic of the captured image, comparing the first noise characteristic to a first predetermined threshold, and detecting debris on an image sensor that outputs the captured image as a result of comparing the first noise characteristic to the first predetermined threshold.

Claims

1. A vehicle computer comprising:

a memory; and

a processor programmed to execute instructions stored in the memory, the instructions include comparing a captured image of a predetermined object to a target image of the predetermined object to quantify a first noise characteristic of the captured image, comparing the first noise characteristic to a first predetermined threshold, and detecting debris on an image sensor that outputs the captured image as a result of comparing the first noise characteristic to the first predetermined threshold.

2. The vehicle computer of claim 1, wherein the first noise characteristic is at least one of a signal-to-noise ratio and a peak signal-to-noise ratio and wherein detecting debris on the image sensor includes detecting debris on the image sensor as a result of determining that the first noise characteristic is below the first predetermined threshold.

3. The vehicle computer of claim 2, wherein the instructions include comparing the captured image to the target image to quantify a second noise characteristic of the captured image, wherein the second noise characteristic includes at least one of a root mean squared error and a mean absolute error, and wherein detecting debris on the image sensor includes detecting debris on the image sensor as a result of determining that the second noise characteristic exceeds a second predetermined threshold.

4. The vehicle computer of claim 3, wherein detecting debris on the image sensor includes detecting debris on the image sensor as a result of the determining that the first noise characteristic is below the first predetermined threshold and the second noise characteristic exceeds the second predetermined threshold.

5. The vehicle computer of claim 1, wherein the instructions include initiating cleaning of the image sensor as a result of detecting debris on the image sensor.

6. The vehicle computer of claim 5, wherein initiating cleaning of the image sensor includes outputting a control signal to a sensor cleaning system.

7. The vehicle computer of claim 1, wherein the instructions include identifying the predetermined object in an original image captured by the image sensor.

8. The vehicle computer of claim 1, wherein the instructions include generating the captured image by manipulating the original image captured by the image sensor.

9. The vehicle computer of claim 8, wherein manipulating the original image includes at least one of cropping the original image and normalizing the original image.

10. The vehicle computer of claim 9, wherein normalizing the original image includes adjusting at least one of an exposure, a brightness, and an orientation of the predetermined object in the original image.

11. The vehicle computer of claim 9, wherein cropping the original image includes removing sections of the original image that do not represent the predetermined object.

12. A method comprising:

comparing a captured image of a predetermined object to a target image of the predetermined object to quantify a first noise characteristic of the captured image;

comparing the first noise characteristic to a first predetermined threshold; and

detecting debris on an image sensor that outputs the captured image as a result of comparing the first noise characteristic to the first predetermined threshold.

13. The method of claim 12, wherein the first noise characteristic is at least one of a signal-to-noise ratio and a peak signal-to-noise ratio and wherein detecting debris on the image sensor includes detecting debris on the image sensor as a result of determining that the first noise characteristic is below the first predetermined threshold.

14. The method of claim 13, further comprising comparing the captured image to the target image to quantify a second noise characteristic of the captured image, wherein the second noise characteristic includes at least one of a root mean squared error and a mean absolute error, and wherein detecting debris on the image sensor includes detecting debris on the image sensor as a result of determining that the second noise characteristic exceeds a second predetermined threshold.

15. The method of claim 14, wherein detecting debris on the image sensor includes detecting debris on the image sensor as a result of the determining that the first noise characteristic is below the first predetermined threshold and the second noise characteristic exceeds the second predetermined threshold.

16. The method of claim 12, further comprising initiating cleaning of the image sensor as a result of detecting debris on the image sensor.

17. The method of claim 12, further comprising identifying the predetermined object in an original image captured by the image sensor.

18. The method of claim 12, further comprising generating the captured image by manipulating the original image captured by the image sensor, wherein manipulating the original image includes at least one of cropping the original image and normalizing the original image.

19. The method of claim 18, wherein normalizing the original image includes adjusting at least one of an exposure, a brightness, and an orientation of the predetermined object in the original image.

20. The method of claim 18, wherein cropping the original image includes removing sections of the original image that do not represent the predetermined object.