Tire tread depth measurement

• US 10,295,333 B2
• Filed: 02/01/2016
• Issued: 05/21/2019
• Est. Priority Date: 12/30/2015
• Status: Active Grant

• Current Assignee: Bosch Automotive Service Solutions LLC (SPX Corporation)
• Original Assignee: Bosch Automotive Service Solutions LLC (SPX Corporation)
• Inventors: Fish, James, Thoppae, Vijai M., Kommera, Sharath
• Primary Examiner(s): Pontius, James M
• Application Number:
  US15/011,786
• Publication Number:
  US 20170190223A1
• Time in Patent Office: 1,205 Days
• CPC Class Codes: G01B 11/22 for measuring depth
• CPC Class Codes: G01M 17/027 using light, e.g. infrared, ultraviolet or holographic techniques
• CPC Class Codes: G06T 17/00 Three dimensional [3D] modelling, e.g. data description of 3D objects
• CPC Class Codes: G06T 7/001 using an image reference approach
• CPC Class Codes: H04N 1/00 Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
• CPC Class Codes: H04N 23/60 Control of cameras or camera modules
• CPC Class Codes: H04N 7/18 Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast

Abstract

This disclosure relates to a system and a method for measuring tire tread depth. The method includes receiving an image of a tire tread recorded using an image-recording device; analyzing the image of the tire tread captured to determine a tire tread depth; determining a status of the tire tread based on the tire tread depth; altering the image of the tire tread captured based on the determined status; and transmitting the altered image to a mobile device.

Claims

1. A method for measuring tire tread depth, the method comprising:

collecting images, with a processor of a computing device, of tires having a variety of tire tread for use with a supervised machine learning algorithm to determine a tire tread depth;

receiving an image, with the processor, of a tire tread recorded using an image-recording device on a mobile device;

receiving a vehicle image taken by the image-recording device by the processor, a vehicle includes the tire tread;

identifying the vehicle with the processor using optical recognition;

analyzing, with the processor using a software, the image of the recorded tire tread to determine a tire tread depth;

determining, with the processor, a status of the tire tread based on the tire tread depth;

altering, with the processor, the image of the recorded tire tread based on the determined status;

transmitting, with the processor, the altered image to the mobile device; and

displaying, on a display of the mobile device, a closest automotive service center with best tire prices.

2. The method of claim 1, wherein analyzing further comprises:

comparing the image of the recorded tire tread with historical tire tread images.

3. The method of claim 1, wherein analyzing further comprises:

collecting data points to generate the algorithm to determine a tire tread depth.

4. The method of claim 3, wherein the algorithm further includes predictive functional algorithm.

5. The method of claim 1, wherein analyzing further comprises:

comparing the image of the recorded tire tread with standard attributes.

6. The method of claim 1, further comprising:

receiving a plurality of images of the tire tread;

generating a three-dimensional model based on the plurality of images of the tire tread; and

determining the tire tread depth using the three-dimensional model.

7. A system for measuring tire tread depth, the system comprising:

a transceiver configured to receive and transmit an image of a tire tread and an image of a vehicle with the tire tread to and from a mobile device;

a computer-readable storage medium configured to store computer-executable instructions; and

a computer processor configured to execute the computer-executable instructions, the computer-executable instructions comprising;

diagnosing, with the processor using a diagnostic application, diagnostic trouble code set in the vehicle;

receiving an image of the vehicle taken by an image-recording device of the mobile device by the processor;

identifying the vehicle with the processor using optical recognition;

collecting images of tires having a variety of tire tread for use with a supervised machine learning algorithm to determine a tire tread depth;

receiving an image of the tire tread recorded using the image-recording device;

analyzing the image of the recorded tire tread to determine a tire tread depth;

determining a status of the recorded tire tread based on the tire tread depth;

altering the image of the recorded tire tread based on the determined status;

transmitting the altered image to the mobile device; and

displaying, on a display of the mobile device, a closest automotive service center with best tire prices.

8. The system of claim 7, wherein the computer-executable instructions further comprise:

comparing the image of the recorded tire tread with historical tire tread images.

9. The system of claim 7, wherein the computer-executable instructions further comprise:

collecting data points to generate an algorithm to determine a tire tread depth.

10. The system of claim 9, wherein the algorithm is a predictive functional algorithm.

11. The system of claim 7, wherein the computer-executable instructions further comprise:

comparing the image of the recorded tire tread with standard attributes.

12. The system of claim 7, wherein the computer-executable instructions further comprise:

receiving a plurality of images of the tire tread;

generating a three-dimensional model based on the plurality of images of the tire tread; and

determining the tire tread depth using the three-dimensional model.

13. A method for measuring tire tread depth, the method comprising:

diagnosing, with a processor using a diagnostic application, diagnostic trouble code set in a vehicle with a tire tread;

receiving an image of the vehicle taken by an image-recording device of a mobile device by the processor;

identifying the vehicle with the processor using optical recognition;

collecting, with the processor, images of tires having a variety of tire tread for use with a supervised machine learning algorithm to determine a tire tread depth;

recording, with the processor, an image of a tire tread using the algorithm to determine a tire tread depth;

analyzing, with the processor, the image of the recorded tire tread to determine a tire tread depth;

determining, with the processor, a status of the recorded tire tread based on the tire tread depth;

altering, with the processor, the image of the recorded tire tread based on the determined status; and

displaying the altered image of the tire tread on a display of the mobile device and a closest automotive service center with the best tire prices.

14. The method of claim 13, further comprising:

transmitting the image of the recorded tire tread to a remote central processing unit; and

receiving from the remote central processing unit an altered image of the tire tread indicating the status of the recorded tire tread.

15. The method of claim 13, wherein analyzing further comprises:

comparing the image of the recorded tire tread with historical tire tread images.

16. The method of claim 13, wherein analyzing further comprises:

collecting data points to generate the algorithm to determine a tire tread depth.

17. The method of claim 16, wherein the algorithm is a predictive functional algorithm.

18. The method of claim 13, wherein analyzing further comprises:

comparing the image of the recorded tire tread with standard attributes.

19. The method of claim 13, further comprising:

receiving a plurality of images of the tire tread;

generating a three-dimensional model based on the plurality of images of the tire tread; and

determining the tire tread depth using the three-dimensional model.

20. The method of claim 19, further comprising:

displaying the three-dimensional model.