METHOD AND SYSTEM FOR DETECTING TRAFFIC LIGHTS

• US 20150294167A1
• Filed: 11/20/2012
• Published: 10/15/2015
• Est. Priority Date: 11/20/2012
• Status: Active Grant

• Current Assignee: Harman International Industries Incorporated (Samsung Electronics Co. Ltd.)
• Original Assignee: Harman International Industries Incorporated (Samsung Electronics Co. Ltd.)
• Inventors: Zhang, Yankun, Hong, Chuyang, Jiang, Ruyi, Weyrich, Norman, Zhou, Yun
• Granted Patent: US 9,811,746 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06T 1/0007 Image acquisition
• CPC Class Codes: G06T 2207/10004 Still image; Photographic image
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06V 10/56 relating to colour
• CPC Class Codes: G06V 20/584 of vehicle lights or traffic lights

Abstract

A method for detecting traffic lights is provided. The method includes: obtaining a color image captured by a camera; converting the color image into a first monochrome scale image; converting the first monochrome scale image into a first binary image; identifying a first set of candidate blobs in the first binary image based on at least one predetermined geometric parameter; and determine whether a first region in the color image, which first region corresponds to one of the first set of candidate blobs, is a green traffic light using a green traffic light classifier. The accuracy and efficiency may be improved.

Claims

1. A method for detecting traffic lights, comprising:

obtaining a color image captured by a camera;

converting the color image into a first monochrome scale image;

converting the first monochrome scale image into a first binary image;

identifying a first set of candidate blobs in the first binary image based on at least one predetermined geometric parameter; and

determining whether a first region in the color image, which first region corresponds to one of the first set of candidate blobs, represents a green traffic light using a green traffic light classifier.

2. The method according to claim 1, wherein the first monochrome scale image is a gray scale image.

3. The method according to claim 2, wherein the color image is converted into the gray scale image based on green channel value.

4. The method according to claim 1 further comprising applying a white top-hat morphology operator on the first monochrome scale image to obtain a second monochrome scale image, and converting the second monochrome scale image into the first binary image.

5. The method according to claim 4, wherein the second monochrome scale image is converted into the first binary image based on a first threshold of brightness.

6. The method according to claim 5, wherein the first threshold of brightness is from about 70% to about 80% of a mean brightness of the second monochrome scale image.

7. The method according to claim 1, wherein the at least one geometric parameter comprises a range of pixel number, a width range, and a range of width to height ratio.

8. The method according to claim 1, wherein the green traffic light classifier is suitable for monochrome scale image, and it is applied on the first monochrome scale image to determine whether the first region represents a green traffic light.

9. The method according to claim 1 further comprising:

converting the color image into a second binary image;

identifying a second set of candidate blobs in the second binary image based on the at least one predetermined geometric parameter; and

determining whether a second region in the color image, which second region corresponds to one of the second set of candidate blobs, represents a red traffic light using a red traffic light classifier, where the color image is converted into the second binary image based on equation (1);

Q=2R−

G−

B  

 

Equation (1)

where R, G, and B respectively represent red channel value, green channel value, and blue channel value of a pixel, if the Q value of the pixel is greater than a second threshold value, the pixel will be set as valid, otherwise the pixel will be set as invalid.

10. The method according to claim 9, wherein the second threshold value is from about 210 to about 230.

11. The method according to claim 9, wherein the red traffic light classifier is suitable for monochrome scale images, and it is applied on the first monochrome scale image to determine whether the second region represents a red traffic light.

12. A system for detecting traffic lights, comprising:

a processing device, configured to;

obtain a color image captured by a camera;

convert the color image into a first monochrome scale image;

convert the first monochrome scale image into a first binary image;

identify a first set of candidate blobs in the first binary image based on at least one predetermined geometric parameter; and

determine whether a first region in the color image, which first region corresponds to one of the first set of candidate blobs, represents a green traffic light using a green traffic light classifier.

13. The system according to claim 12, wherein the first monochrome scale image is a gray scale image.

14. The system according to claim 13, wherein the color image is converted into the gray scale image based on green channel value.

15. The system according to claim 12, wherein the processing device is further configured to apply a white top-hat morphology operator on the first monochrome scale image to obtain a second monochrome scale image, and convert the second monochrome scale image into the first binary image.

16. The system according to claim 15, wherein the second monochrome scale image is converted into the first binary image based on a first threshold of brightness.

17. The system according to claim 16, wherein the first threshold of brightness is from about 70% to about 80% of a mean brightness of the second monochrome scale image.

18. The system according to claim 12, wherein the at least one geometric parameter comprises a range of pixel number, a width range, and a range of width to height ratio.

19. The system according to claim 12, wherein the processing device is further configured to:

convert the color image into a second binary image;

identify a second set of candidate blobs in the second binary image based on the at least one predetermined geometric parameter; and

determine whether a second region in the color image, which second region corresponds to one of the second set of candidate blobs, represents a red traffic light using a red traffic light classifier, where the color image is converted into the second binary image based on equation (1);

Q=2R−

G−

B  

 

Equation (1)

where R, G, and B respectively represent red channel value, green channel value, and blue channel value of a pixel, if the Q value of the pixel is greater than a second threshold value, the pixel will be set as valid, otherwise the pixel will be set as invalid.

20. The system according to claim 19, wherein the second threshold value is from about 210 to about 230.

21. The system according to claim 19, wherein the red traffic light classifier is suitable for monochrome scale images, and is applied on the first monochrome scale image to determine whether the second region represents a red traffic light.