Detecting Ground Geographic Features in Images Based on Invariant Components

• US 20100329508A1
• Filed: 06/24/2009
• Published: 12/30/2010
• Est. Priority Date: 06/24/2009
• Status: Active Grant

• Current Assignee: HERE Global B.V. (Nokia Corporation)
• Original Assignee: HERE Global B.V. (Nokia Corporation)
• Inventors: Chen, Xin, Yang, Xiangheng
• Granted Patent: US 8,953,838 B2
• Time in Patent Office: Days
• US Class Current: 382/103
• CPC Class Codes: G06V 20/38 Outdoor scenes
• CPC Class Codes: G06V 20/39 Urban scenes
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle
• 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

Abstract

Systems, devices, features, and methods for detecting geographic features in images, such as, for example, to develop a navigation database are disclosed. For example, a method of detecting a path marking from collected images includes collecting a plurality of images of geographic areas along a path. An image of the plurality of images is selected. Components that represent an object on the path in the selected image are determined. In one embodiment, the determined components are independent or invariant to scale of the object. The determined components are compared to reference components in a data library. If the determined components substantially meet a matching threshold with the reference components, the object in the selected image is identified to be a path marking corresponding to the reference components in the data library.

Claims

1. A method of detecting a geographic feature on a road in an image to develop a navigation database, the method comprising:

capturing a plurality of images along roads, the plurality of images captured via a camera mounted on a vehicle;

determining scale-invariant features of each of the plurality of images, the scale-invariant features determined as a function of a scale-invariant feature transform;

comparing the determined scale-invariant features with reference scale-invariant features to determine whether a desired geographic object is included in at least one of II the plurality of images, the reference invariant features corresponding to the desired geographic object;

identifying at least one of the plurality of images determined to include the desired geographic object as a function of the comparison between the determined scale-invariant features and the reference scale-invariant features, the desired geographic object being a geographic feature on a road in the at least one identified image; and

developing a navigation database based on identifying the at least one of the plurality of images determined to include the desired geographic object.

2. The method of claim 1, wherein the desired geographic object comprises a cross-walk pattern on the road.

3. The method of claim 2, wherein the cross-walk pattern comprises a zebra pattern.

4. The method of claim 1, wherein the desired geographic object comprises a road marking.

5. The method of claim 4, wherein the road marking comprises a turn restriction marking, an informational marking, or a marking within a lane.

6. The method of claim 1, wherein the determined scale-invariant features comprise amplitude extrema points.

7. The method of claim 1, wherein the determined scale-invariant features comprise gradient vectors.

8. A method of detecting a path marking from collected images, the method comprising:

collecting a plurality of images of geographic areas along a path;

selecting an image of the plurality of images;

determining components that represent an object on the path in the selected image, the determined components being independent to scale of the object;

comparing the determined components to reference components in a data library; and

if, based on the comparison, the determined components substantially meet a matching threshold with the reference components, identifying the object in the selected image to be a path marking corresponding to the reference components in the data library.

9. The method of claim 8, wherein the path marking comprises a zebra cross-walk pattern.

10. The method of claim 8, wherein the determined components are independent to rotation of the object.

11. The method of claim 8, wherein the determined components are independent to illumination of the object.

12. The method of claim 8, further comprising:

identifying a desired road feature in a reference image of the plurality of images;

determining the reference components that correspond to the desired road feature in the reference image, the reference components being independent to scale and to rotation of the desired road feature; and

storing the reference components in the data library.

13. The method of claim 8, further comprising:

if the object in the selected image is identified to be the path marking, sending a text file to a map developer, the text file identifying the selected image as an image with the path marking.

14. The method of claim 8, further comprising:

developing a navigation database based on identifying the object in the selected image to be the road marking.

15. A computer-readable medium configured to store a computer program that performs a method of identifying a geographic feature in an image corresponding to a road, the method comprising:

identifying a desired road feature in an image of a road, the road feature on the road;

determining data components that correspond to the desired road feature, the data components being scale-invariant components;

storing the data components that correspond to the desired road feature in a navigation library of a map database developer;

selecting another image representing another road;

determining scale-invariant components of the other image;

comparing the determined scale-invariant components of the other image with the data components stored in the navigation library to determine if the other image includes a feature corresponding to the desired road feature.

16. The method of claim 15, wherein the desired road feature comprises a cross-walk pattern in the image.

17. The method of claim 15, further comprising:

clustering at least some of the determined scale-invariant components of the other image; and

filtering the determined scale-invariant components of the other image that are not part of the clustered scale-invariant components.

18. The method of claim 17, wherein the clustered components correspond to an area on the other road in the other image.

19. The method of claim 15, wherein determining the scale-invariant components of the desired road feature comprises determining amplitude extrema in regions of a difference image, the difference image comprising an image generated from a difference between the image of the road and a blurred image of the road.

20. The method of claim 15, wherein the data components being substantially invariant to rotation and to brightness.

21. The method of claim 15, further comprising:

if it is determined that the other image includes the feature corresponding to the desired road feature, providing identification of the selected other image to the map database developer.