TRAFFIC LIGHT DETECTION

• US 20160148063A1
• Filed: 08/20/2013
• Published: 05/26/2016
• Est. Priority Date: 08/20/2013
• Status: Active Grant

• Current Assignee: Harman International Industries Incorporated (Samsung Electronics Co. Ltd.)
• Original Assignee: Harman International Industries Incorporated (Samsung Electronics Co. Ltd.)
• Inventors: Hong, Chuyang, Zhang, Yankun, Jiang, Ruyi, Zhou, Yun
• Granted Patent: US 9,953,229 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 18/24 Classification techniques
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 7/90 Determination of colour characteristics
• CPC Class Codes: G06V 20/582 of traffic signs
• CPC Class Codes: G06V 20/584 of vehicle lights or traffic lights
• CPC Class Codes: G08G 1/09623 Systems involving the acquisition of information from passive traffic signs by means mounted on the vehicle G08G1/0967 takes precedence

Abstract

A method and a system for traffic light detection are provided. The method may include: obtaining a color image; calculating pixel response values for pixels of the color image, respectively, where each of the pixel response values may be calculated using R, G, and B values of a corresponding pixel directly, such that pixel response values of red traffic light pixels are substantially distributed on a first side of a predetermined range and pixel response values of green traffic light pixels are substantially distributed on a second side of the predetermined range which is opposite to the first side; identifying pixels whose pixel response values are distributed on the first side or the second side as candidate pixels; identifying candidate blobs based on the candidate pixels; and verifying whether the candidate blobs are traffic lights. Efficiency and reliability may be improved.

Claims

1. A method for traffic light detection, comprising:

obtaining a color image;

calculating pixel response values for pixels of the color image, respectively, where each of the pixel response values is calculated using R, G, and B values of a corresponding pixel directly, such that pixel response values of red traffic light pixels are substantially distributed on a first side of a predetermined range and pixel response values of green traffic light pixels are substantially distributed on a second side of the predetermined range which is opposite to the first side;

identifying pixels whose pixel response values are distributed on the first side or the second side as candidate pixels;

identifying candidate blobs based on the candidate pixels; and

verifying whether the candidate blobs are traffic lights.

2. The method according to claim 1, wherein pixel response values of pixels other than red traffic light pixels and green traffic light pixels are substantially distributed within the predetermined range.

3. The method according to claim 1, wherein each of the pixel response values is calculated based on multiplication of a first component and a second component of a corresponding pixel, where the first component indicates a tendency of the pixel response value, and the second component is able to amply the tendency if the tendency is towards the first side or the second side.

4. The method according to claim 3, wherein the first component is calculated based on summation of a third, a fourth, and a fifth components which are respectively based on R, G and B values of the corresponding pixel, where the third component has a first sign, and the fourth and fifth components have a second sign which is opposite to the first sign.

5. The method according to claim 4, wherein the third component is k1*R, the fourth component is −

k2*G, and the fifth component is −

k3*B, where k1, k2 and k3 are set such that the tendency is substantially towards the first side if the corresponding pixel is a red traffic light pixel and the tendency is substantially towards the second side if the corresponding pixel is a green traffic light pixel.

6. The method according to claim 3, wherein the second component is calculated based on summation of a sixth and a seventh components which are respectively based on R and G values of the corresponding pixel, where the sixth and seventh components have the same sign.

7. The method according to claim 6, wherein the sixth component is k4*R and the seventh component is k5*G, where k4 and k5 are set such that the pixel response value is substantially on the first side if the corresponding pixel is a red traffic light pixel, and the pixel response value is substantially on the second side if the corresponding pixel is a green traffic light pixel.

8. The method according to claim 1, wherein identifying the candidate blobs based on the candidate pixels comprises:

identifying a first set of blobs based on the candidate pixels; and

identifying the candidate blobs from the first set of blobs, where each of the first set of blobs is determined whether or not a member of the candidate blobs based on pixel response values of its pixels and its surrounding pixels.

9. A system for traffic light detection, comprising a processing device configured to:

obtain a color image;

calculate pixel response values for pixels of the color image, respectively, where each of the pixel response values is calculated using R, G, and B values of a corresponding pixel directly, such that pixel response values of red traffic light pixels are substantially distributed on a first side of a predetermined range and pixel response values of green traffic light pixels are substantially distributed on a second side of the predetermined range which is opposite to the first side;

identify pixels whose pixel response values are distributed on the first side or the second side as candidate pixels;

identify candidate blobs based on the candidate pixels; and

verify whether the candidate blobs are traffic lights.

10. The system according to claim 9, wherein pixel response values of pixels other than red traffic light pixels and green traffic light pixels are substantially distributed within the predetermined range.

11. The system according to claim 9, wherein the processing device is configured to calculate each of the pixel response values based on multiplication of a first component and a second component of a corresponding pixel, where the first component indicates a tendency of the pixel response value, and the second component is able to amply the tendency if the tendency is towards the first side or the second side.

12. The system according to claim 11, wherein the first component is calculated based on summation of a third, a fourth, and a fifth components which are respectively based on R, G and B values of the corresponding pixel, where the third component has a first sign, and the fourth and fifth components have a second sign which is opposite to the first sign.

13. The system according to claim 12, wherein the third component is k1*R, the fourth component is −

k2*G, and the fifth component is −

k3*B, where k1, k2 and k3 are set such that the tendency is substantially towards the first side if the corresponding pixel is a red traffic light pixel and the tendency is substantially towards the second side if the corresponding pixel is a green traffic light pixel.

14. The system according to claim 11, wherein the second component is calculated based on summation of a sixth and a seventh components which are respectively based on R and G values of the corresponding pixel, where the sixth and seventh components have the same sign.

15. The system according to claim 14, wherein the sixth component is k4*R and the seventh component is k5*G, where k4 and k5 are set such that the pixel response value is substantially on the first side if the corresponding pixel is a red traffic light pixel, and the pixel response value is substantially on the second side if the corresponding pixel is a green traffic light pixel.

16. The system according to claim 9, wherein the processing device is configured to identify the candidate blobs by:

identifying a first set of blobs based on the candidate pixels; and

identifying the candidate blobs from the first set of blobs, where each of the first set of blobs is determined whether or not a member of the candidate blobs based on pixel response values of its pixels and its surrounding pixels.

17. A system for traffic light detection, comprising:

means for calculating pixel response values for pixels of a color image, respectively, where each of the pixel response values is calculated using R, G, and B values of a corresponding pixel directly, such that pixel response values of red traffic light pixels are substantially distributed on a first side of a predetermined range and pixel response values of green traffic light pixels are substantially distributed on a second side of the predetermined range which is opposite to the first side;

means for identifying pixels whose pixel response values are distributed on the first side or the second side as candidate pixels;

means for identifying candidate blobs based on the candidate pixels; and

means for verifying whether the candidate blobs are traffic lights.

18. The system according to claim 17, wherein the color image is captured by a camera, the camera mounted on a vehicle.

19. The system according to claim 17, wherein verifying whether the candidate blobs are traffic lights includes identifying a set of blobs from the candidate blobs based on one or more geometric parameters of each of the set of blobs, the geometric parameters including a pixel number based on an image resolution, a height, a width, and a width to height ratio.

20. The system according to claim 19, wherein verifying whether the candidate blobs are traffic lights further comprises calculating a probability of each of the set of blobs based on a first pixel response value for pixels within an ego segment and a second pixel response value for pixels within an ambient segment, the ego segment enclosing each of the set of blobs and the ambient segment partially overlapping with the ego segment.