SATURATION-BASED SHADE-LINE DETECTION

• US 20110133510A1
• Filed: 12/07/2009
• Published: 06/09/2011
• Est. Priority Date: 12/07/2009
• Status: Abandoned Application

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations Incorporated (General Motors Company)
• Inventors: Zhang, Wende
• Application Number:
  US12/632,544
• Publication Number:
  US 20110133510A1
• Time in Patent Office: Days
• US Class Current: 296/97.4
• CPC Class Codes: G06T 2207/30268 Vehicle interior
• CPC Class Codes: G06T 7/12 Edge-based segmentation
• CPC Class Codes: H04N 5/202 Gamma control circuits for controlling camera response irrespective of the scene brightness H04N23/82
• CPC Class Codes: H04N 5/21 Circuitry for suppressing or minimising disturbance, e.g. moiré or halo

Abstract

A system and method for detecting a sun-shade line on a vehicle driver'"'"'s face so as to automatically position a sun blocker at the appropriate location to block the sun. The method includes providing a detected image of the vehicle driver using, for example, a camera. A saturation analysis is performed on the detected image to generate a saturation image that includes bright dots and dark dots as a binary image. The method then performs a region enhancement of the saturation image to filter the saturation image. A histogram analysis is performed on the filtered saturation image to generate a graph that identifies a count of the bright dots in the image on a row-by-row basis. The method then performs a sharp change analysis on the graph to identify the largest transition from a row with the most dark dots to a row with the most bright dots to identify the sun-shade line.

Claims

1. A method for determining the location of a sun-shade line on an object using a saturation-based approach, said method comprising:

providing a detected image of the object;

performing a saturation analysis on the detected image to generate a binary saturation image that includes bright dots and dark dots;

performing a region enhancement on the saturation image to filter the saturation image and generate a filtered saturation image;

performing a histogram analysis on the filtered saturation image to identify a count of the bright dots on a row-by-row basis in the image; and

performing a sharp change analysis on results from the histogram analysis to identify the largest transition from a row with dark dots to a row with bright dots that defines the sun-shade line.

2. The method according to claim 1 wherein providing a detected image includes using a camera.

3. The method according to claim 1 wherein performing a saturation analysis includes comparing each pixel in the detected image to a brightness threshold.

4. The method according to claim 1 wherein performing the sharp change analysis includes using a differential filter.

5. The method according to claim 1 wherein the object is a vehicle driver.

6. The method according to claim 5 further comprising positioning a sun blocker in response to the identified position of the sun-shade line so that eyes of the vehicle driver are within a shadow caused by the sun blocker.

7. The method according to claim 1 further comprising determining the location of the sun-shade line using an active detection approach that is different than the saturation-based approach, wherein the saturation-based approach and the active detection approach are combined to determine the location of the sun-shade line.

8. The method according to claim 7 wherein the location of the sun-shade line is determined based on a weighting between the combined estimation approaches and a predicted location of the sun-shade line, where the weighting is determined by a consistency factor that increases as the determination of the location of the sun-shade line by the saturation-based approach and the active detection approach becomes closer, where the predicted location of the sun-shade line becomes less important, and decreases as the determination of the location of the sun-shade line by the saturation-based approach and the active detection approach becomes farther apart, where the predicted location of the sun-shade line becomes more important.

9. A method for determining the location of a sun-shade line on a vehicle driver using a saturation-based approach, said method comprising:

providing a detected image of the vehicle driver using a camera;

performing a saturation analysis on the detected image to generate a binary saturation image that includes bright dots and dark dots, wherein the saturation analysis includes comparing each pixel in the detected image to a brightness threshold;

performing a region enhancement on the saturation image to filter the saturation image and generate a filtered saturation image;

performing a histogram analysis on the filtered saturation image to generate a graph that identifies a count of the bright dots on a row-by-row basis in the image; and

performing a sharp change analysis on the graph using a differential filter to identify a most negative location in the graph that is the largest transition from a row with black dots to a row with bright dots to identify the sun-shade line.

10. The method according to claim 9 further comprising positioning a sun blocker in response to the identified position of the sun-shade line so that eyes of the vehicle driver are within a shadow caused by the sun blocker.

11. The method according to claim 9 further comprising determining the location of the sun-shade line using an active detection approach that is different than the saturation-based approach, wherein the saturation-based approach and the active detection approach are combined to determine the location of the sun-shade line.

12. The method according to claim 11 wherein the location of the sun-shade line is determined based on a weighting between the combined estimation approaches and a predicted location of the sun-shade line, where the weighting is determined by a consistency factor that increases as the determination of the location of the sun-shade line by the saturation-based approach and the active detection approach becomes closer, where the predicted location of the sun-shade line becomes less important, and decreases as the determination of the location of the sun-shade line by the saturation-based approach and the active detection approach becomes farther apart, where the predicted location of the sun-shade line becomes more important.

13. A system for determining the location of a sun-shade line on a vehicle driver using a saturation-based approach, said system comprising:

a camera for providing a detected image of the driver;

means for performing a saturation analysis on the detected image to generate a binary saturation image that includes bright dots and dark dots;

means for performing a region enhancement on the saturation image to filter the saturation image and generate a filtered saturation image;

means for performing a histogram analysis on the filtered saturation image to identify a count of the bright dots on a row-by-row basis in the image; and

means for performing a sharp change analysis on results from the histogram analysis to identify the largest transition from a row with dark dots to a row with bright dots that defines the sun-shade line.

14. The system according to claim 13 wherein the means for performing a saturation analysis compares each pixel in the detected image to a brightness threshold.

15. The system according to claim 13 wherein the means for performing the sharp change analysis uses a differential filter.

16. The system according to claim 13 further comprising means for positioning a sun blocker in response to the identified position of the sun-shade line so that eyes of the vehicle driver are within a shadow caused by the sun blocker.

17. The system according to claim 13 further comprising means for determining the location of the sun-shade line using an active detection approach that is different than the saturation-based approach, and means for combining the saturation-based approach and the active detection approach as a combined estimation approach that determines the location of the sun-shade line.

18. The system according to claim 17 wherein the means for combining the saturation-based approach and the active detection approach to determine the location of the sun-shade line is based on a weighting between the combined estimation approach and a predicted location of the sun-shade line, where the weighting is determined by a consistency factor that increases as the determination of the location of the sun-shade line by the saturation-based approach and the active detection approach becomes closer, where the predicted location of the sun-shade line becomes less important, and decreases as the determination of the location of the sun-shade line by the saturation-based approach and the active detection approach becomes farther apart, where the predicted location of the sun-shade line becomes more important.

19. A method for determining the location of a line on an object, said method comprising:

using a saturation-based approach that includes;

providing a detected image of the object;

performing a saturation analysis on the detected image to generate a binary saturation image that includes bright dots and dark dots;

performing a region enhancement on the saturation image to filter the saturation image and generate a filtered saturation image;

performing a histogram analysis on the filtered saturation image to identify a count of the bright dots on a row-by-row basis in the image;

performing a sharp change analysis on results from the histogram analysis to identify the largest transition from a row with dark dots to a row with bright dots that defines the line; and

using an active detection approach that is different than the saturation-based approach, wherein the saturation-based approach and the active detection approach are combined to determine the location of the line.

20. The method according to claim 19 wherein the location of the line is determined based on a weighting between the combined estimation approaches and a predicted location of the line, where the weighting is determined by a consistency factor that increases as the determination of the location of the line by the saturation-based approach and the active detection approach becomes closer, where the predicted location of the line becomes less important, and decreases as the determination of the location of the line by the saturation-based approach and the active detection approach becomes farther apart, where the predicted location of the line becomes more important.