PIXEL-BASED TEXTURE-LESS CLEAR PATH DETECTION

• US 20090295917A1
• Filed: 05/29/2009
• Published: 12/03/2009
• Est. Priority Date: 04/24/2008
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations Incorporated (General Motors Company)
• Inventors: Naik, Sanjeev M., Zhang, Wende
• Granted Patent: US 8,634,593 B2
• Time in Patent Office: Days
• US Class Current: 348/119
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2420/42 Image sensing, e.g. optical camera
• CPC Class Codes: G06V 10/56 relating to colour
• CPC Class Codes: G06V 20/588 Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
• CPC Class Codes: G08G 1/165 for passive traffic, e.g. including static obstacles, trees
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes
• CPC Class Codes: G08G 1/167 Driving aids for lane monitoring, lane changing, e.g. blind spot detection

Abstract

A method for detecting a clear path of travel for a vehicle utilizing analysis of a plurality of images generated by a camera device located upon the vehicle includes monitoring the images wherein each image comprises a plurality of pixels, utilizing a texture-less processing scheme to analyze the images including filtering the image to separate portions of the image indicating a clear surface upon which a potential road surface can be estimated from other portions of the image that do not indicate a potential road surface. The clear path is determined based upon the clear surface and the clear path is utilized to operate the vehicle.

Claims

1. Method for detecting a clear path of travel for a vehicle utilizing analysis of a plurality of images generated by a camera device located upon the vehicle, the method comprising:

monitoring the images, each image comprising a plurality of pixels;

utilizing a texture-less processing scheme to analyze the images comprising

in each image, filtering the image to separate portions of the image indicating a clear surface upon which a potential road surface can be estimated from other portions of the image that do not indicate a potential road surface; and

determining a clear path based upon the clear surface.

2. The method of claim 1, wherein filtering the image to separate the portions of the image indicating the clear surface upon which the potential road surface can be estimated from other portions of the image that do not indicate a potential road surface comprises:

filtering an area below a horizon line on the image from an area above the horizon line.

3. The method of claim 1, wherein filtering the image to separate the portions of the image indicating the clear surface upon which the potential road surface can be estimated from other portions of the image that do not indicate a potential road surface comprises:

filtering pixels in the image based upon comparing a color intensity of the pixels to a color intensity threshold based upon a color distribution mean.

4. The method of claim 3, wherein each of the pixels comprises a plurality of color intensities;

wherein the color intensity threshold based upon the color distribution mean comprises a color intensity threshold for each of the plurality of color intensities; and

wherein filtering pixels in the image based upon comparing a color intensity of the pixels to a color intensity threshold based upon a color distribution mean comprises

comparing each of the plurality of color intensities for each of the pixels to the color intensity threshold for each of the plurality of color intensities, and

filtering each of the pixels based upon eliminating the pixel when one of the pluralities of color intensities is greater than the color intensity threshold associated with the color intensity.

5. The method of claim 4, wherein the color distribution mean for the color intensity threshold associated with one of the pluralities of color intensities associated color intensity is an average color intensity distributed in the image.

6. The method of claim 5, further comprising:

adapting the color distribution mean for the associated color intensity based upon the monitored images.

7. The method of claim 4, wherein a first color intensity is a red intensity, a second color intensity is a green intensity, and a third color intensity is blue intensity and wherein each pixel comprises a first, second, and third color intensity, and filtering the pixel when the difference between a red intensity of the pixel and a red color distribution mean is greater than a red intensity threshold, and the difference between a green intensity of the pixel and a green color distribution mean is greater than a green intensity threshold, and the difference between a blue intensity of the pixel and a blue color distribution mean is greater than a blue intensity threshold.

8. The method of claim 1, wherein filtering the image to separate the portions of the image indicating the clear surface upon which the potential road surface can be estimated from other portions of the image that do not indicate a potential road surface comprises:

analyzing based upon differencing sequential images.

9. The method of claim 8, wherein differencing sequential images comprises:

determining a difference between individual pixels on a current image and corresponding individual pixels on a previous image.

10. The method of claim 9, wherein the difference is determined by subtracting color intensities associated with a pixel from corresponding color intensities to determine a color intensity difference.

11. The method of claim 9, further comprising:

filtering the individual pixels comprising eliminating pixels when the difference between individual pixels on a current image and corresponding individual pixels on a previous image is exceeds a predetermined threshold.

12. The method of claim 9, wherein the previous image is adjusted based upon vehicle motion.

13. The method of claim 1, wherein filtering the image to separate the portions of the image indicating the clear surface upon which the potential road surface can be estimated from other portions of the image that do not indicate a potential road surface comprises:

filtering based upon identifying pixels representing edges.

14. The method of claim 13, wherein filtering based upon identifying pixels representing edges comprises applying a Sobel filter.

15. The method of claim 1, wherein filtering the image to separate the portions of the image indicating the clear surface upon which the potential road surface can be estimated from other portions of the image that do not indicate a potential road surface comprises:

creating a plurality of filtered images; and

fusing the filtered images together to determine the clear surface.

16. The method of claim 15, wherein fusing the filtered images together comprises:

determining pixel locations included on each of the plurality of filtered images;

comparing pixels at the pixel locations with corresponding pixel locations on the plurality of filtered images; and

including the pixel when each of the plurality of filtered images contains the pixel at the corresponding pixel location.

17. Method for detecting a clear path of travel for a vehicle utilizing analysis of a plurality of images generated by a camera device located upon the vehicle, the method comprising:

monitoring the images;

utilizing a texture-less control scheme to analyze the images comprising

filtering an area below a horizon line on the image from an area above the horizon line,

filtering pixels in the image based upon comparing a color intensity of the pixels to a color intensity threshold based upon a color distribution mean,

filtering based upon differencing sequential images,

filtering based upon identifying pixels representing edges,

determining a clear surface based upon the filtering and determining a clear path based upon the clear surface, and

utilizing the clear path to operate the vehicle;

utilizing a texture rich control scheme to analyze the images comprising

identifying a set of interest points from the plurality of pixels in each of two images, the two images comprising a current image and a preceding image,

matching pairs of interest points from the set of interest points from the current image and the set of interest points from the preceding image, wherein each of the matched pairs is estimated to correspond to a single viewed feature,

filtering the matched pairs of interest points to select a high quality set of matched pairs, and

generating a three dimensional map of features in the view based upon the high quality set of matched pairs;

determining a clear path based upon the texture rich control scheme and the texture-less control scheme; and

utilizing the clear path to operate the vehicle.

18. Apparatus for detecting a clear path of travel for a vehicle utilizing analysis of a plurality of images generated by a camera device located upon the vehicle, the apparatus comprising:

the camera device; and

a control module monitoring the images from the camera device and monitoring the images, each image comprising a plurality of pixels,

utilizing a texture-less processing scheme to analyze the images comprising

in each image, filtering the image to separate portions of the image indicating a clear surface upon which a potential road surface can be estimated from other portions of the image that do not indicate a potential road surface, and

determining a clear path based upon the clear surface.