Detecting Geographic Features in Images Based on Invariant Components

• US 20100329504A1
• Filed: 06/24/2009
• Published: 12/30/2010
• Est. Priority Date: 06/24/2009
• Status: Active Grant

• Current Assignee: HERE Global B.V. (HERE Holding Corporation)
• Original Assignee: HERE Global B.V. (HERE Holding Corporation)
• Inventors: Chen, Xin
• Granted Patent: US 8,761,435 B2
• Time in Patent Office: Days
• US Class Current: 382/100
• CPC Class Codes: G06V 20/582 of traffic signs
• 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: G06V 20/63 Scene text, e.g. street names
• CPC Class Codes: G06V 30/10 Character recognition
• CPC Class Codes: G06V 30/18143 Extracting features based on salient regional features, e.g. scale invariant feature transform [SIFT] keypoints

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 text from collected images includes collecting a plurality of images of geographic areas along a road or path. An image of the plurality of images is selected. Components that represent a feature about the road or path in the selected image are determined. In one embodiment, the components are independent or invariant to scale of the feature. The determined components are compared to reference components in a data library. If the determined components substantially match with the reference components, the feature in the selected image is identified to be a text character (e.g., of a road sign) corresponding to at least some of the reference components in the data library.

Claims

1. A computer-readable medium configured to store a computer program that performs a method of detecting a road sign in an image for development of a navigation database, the method comprising:

receiving a plurality of images of 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 road sign is included in at least one of the plurality of images, the reference scale-invariant features corresponding to a text character; and

identifying at least one of the plurality of images determined to include the road sign as a function of the comparison between the determined scale-invariant features and the reference scale-invariant features, the road sign including the text character.

2. The method of claim 1, wherein the road sign comprises a road sign with an uncommon text sequence.

3. The method of claim 1, wherein the road sign comprises an expressway road sign.

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

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

6. The method of claim 1, wherein identifying the at least one of the plurality of images includes generating a text file, the text file including location information of where the identified image was taken.

7. A method of detecting text from collected road images to develop a map navigation database, the method comprising:

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

selecting an image of the plurality of images;

determining components that represent a feature about the road in the selected image, the components being independent to scale of the feature;

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

if, based on the comparison, the determined components substantially match with the reference components, identifying the feature in the selected image to be at least one text character corresponding to the reference components in the data library; and

developing a map navigation database based on identifying the feature in the selected image to be the at least one text character.

8. The method of claim 7, wherein the at least one text character comprises at least one letter or at least one number.

9. The method of claim 7, wherein developing the map navigation database includes storing data representing a geographic object associated with the identified at least one text character in the map navigation database.

10. The method of claim 7, wherein the determined components are substantially independent to brightness of the feature.

11. The method of claim 7, wherein the determined components are substantially independent to rotation of the feature.

12. The method of claim 7, further comprising:

identifying a letter or number in a reference image of the plurality of images;

determining the reference components that represent the letter or number in the reference image, the reference components being independent to scale and to rotation of the letter or number; and

storing the reference components in the data library.

13. A method of identifying text in an image to determine a path feature, the method comprising:

identifying a letter or number in an image of a path;

determining data components that correspond to the letter or number, the data components being scale-invariant components;

storing the data components that correspond to the letter or number in a navigation library of a map database developer;

selecting another image representing another path;

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 character corresponding to the letter or number.

14. The method of claim 13, further comprising:

if it is determined that the other image includes the character, identifying the other image as including a path sign.

15. The method of claim 13, further comprising:

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

before comparing, filtering determined scale-invariant components that are not part of the clustered components.

16. The method of claim 13, wherein determining the scale-invariant components of the letter or the number 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 path and a blurred image of the path.

17. The method of claim 13, wherein the data components being substantially invariant to rotation.

18. The method of claim 13, wherein the data components being substantially invariant to illumination.

19. The method of claim 13, further comprising:

if it is determined that the other image includes the character, providing identification of the selected other image to the map database developer.

20. The method of claim 19, wherein providing the identification comprises providing a text file including location information associated with the other image.