Model-based object classification and target recognition

• US 8,005,261 B2
• Filed: 09/16/2002
• Issued: 08/23/2011
• Est. Priority Date: 09/15/2001
• Status: Expired due to Fees

• Current Assignee: Airbus Defence and Space GmbH
• Original Assignee: EADS Deutschland GmbH (Airbus SE)
• Inventors: Eggers, Helmuth, Baur, Henrik, Krüger, Lars, Ott, Rainer
• Primary Examiner(s): Repko; Jason M
• Assistant Examiner(s): Thirugnanam; Gandhi
• Application Number:
  US10/488,927
• Publication Number:
  US 20040267682A1
• Time in Patent Office: 3,263 Days
• Field of Search: None
• US Class Current: 382/103
• CPC Class Codes: G06V 10/255 Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
• CPC Class Codes: G06V 20/62 Text, e.g. of license plates, overlay texts or captions on TV images
• CPC Class Codes: G06V 2201/07 Target detection

Abstract

Method for at least one of model-based classification and target recognition of an object. The method includes recording an image of an inanimate object, determining a feature that represents a part of the inanimate object, determining at least one condition associated with the feature that indicates an applicability of the feature based on at least one of geometry of the object, distance of the object from a camera, illumination conditions, contrast, speed of the object, height of the object, and relative position of the object to a camera, and carrying out the at least one of classification and target recognition of the object by recording the feature when the at least one condition indicates the applicability of the feature. At least one of object classification and target recognition is carried out for a feature of the object that is visible and recordable according to the position of the object. The recording, the determining the feature, the determining the at least one condition, and the carrying out are implemented on a computer.

Claims

1. A method for at least one of model-based classification and target recognition of an object, the method comprising:

recording an image of an inanimate object;

determining a feature that represents a recognized part of the inanimate object;

determining at least one condition associated with the feature that indicates an applicability of the feature based on at least one of;

geometry of the object, distance of the object from a camera, illumination conditions, contrast, speed of the object, height of the object, and relative position of the object to a camera;

carrying out the at least one of classification and target recognition of the object by recording the feature when the at least one condition indicates the applicability of the feature; and

matching a position created by a movement of the inanimate object in space to the position of the inanimate object in the image,

wherein at least one of object classification and target recognition is carried out for a feature of the object that is visible and recordable according to the position of the object,

wherein the determining the at least one condition occurs before the determining the feature, and

wherein the recording, the determining the feature, the determining the at least one condition, and the carrying out are implemented on a computer.

2. The method according to claim 1, wherein the determining of the feature that represents a part of the object comprises determining a plurality of features, wherein the determining of the at least one condition comprises determining at least one condition for each of the plurality of features, and wherein the carrying out the at least one classification and target recognition of the object comprises at least one of classifying and target recognizing of the object through the detection of the plurality of features.

3. The method according to claim 1, wherein the determining of the feature that represents a part of the object comprises determining a plurality of features.

4. The method according to claim 3, wherein the determining of at least one condition comprises determining at least one condition for each of the plurality of features.

5. The method according to claim 3, wherein the carrying out the at least one classification and target recognition of the object comprises at least one of classifying and target recognizing of the object through the detection of the plurality of features.

6. The method according to claim 1, wherein a programmable algorithm is associated with the at least one condition and the method further comprises programming the algorithm as desired.

7. The method according to claim 1 further comprising:

preprocessing for the detection of a specific feature;

testing, before the preprocessing for the detection of the specific feature, whether the preprocessing for the detection of the specific feature has been carried out in connection with an other feature; and

using, when preprocessing for the detection of the specific feature has been carried out for the other feature, the preprocessing of the another feature as the preprocessing for the detection of the specific feature.

8. The method according to claim 7 further comprising:

storing the preprocessing in a cache memory.

9. The method according to claim 7, wherein the specific feature is one of a left edge and right edge of an object and the preprocessing of each of these features comprises edge image preprocessing.

10. The method according to claim 7 further comprising:

storing all reusable preprocessing as a sequence of compilation.

11. The method according to claim 8, wherein the cache is not restricted to a type of preprocessing.

12. The method according to claim 1, wherein the at least one of object classification and target recognition is carried out for a feature of the object that is visible and recordable according to the position of the object with reference to a camera.

13. The method according to claim 1, wherein the object is an aircraft.

14. The method according to claim 1, wherein the object is a helicopter.

15. The method according to claim 1, further comprising:

detecting the inanimate object in the image using a region of interest (ROI); and

matching a movement of the object in space to the position of the object in the image.

16. The method according to claim 15, further comprising estimating a change in position of the object in space.

17. A method for model-based classification and target recognition of an object, the method comprising:

recording an image of an inanimate object;

detecting the inanimate object in the image using a region of interest (ROI);

determining a feature that represents a recognized part of the inanimate object;

determining at least one condition associated with the feature that indicates an applicability of the feature based on at least one of;

geometry of the object, distance of the object from a camera, illumination conditions, contrast, speed of the object, height of the object, and relative position of the object to a camera;

carrying out the at least one classification and target recognition of the object by recording the feature when the condition indicates the applicability of the feature;

extracting from the image only the feature which has been linked to the at least one condition such that object classification need not be carried out for a feature of the object that is not visible; and

matching a position created by a movement of the inanimate object in space to the position of the inanimate object in the image;

wherein the recording, the determining the feature, the determining the at least one condition, and the carrying out are implemented on a computer.

18. The method according to claim 17, wherein the determining of the feature that represents a part of the object comprises determining a plurality of features, wherein the determining of the at least one condition comprises determining at least one condition for each of the plurality of features, and wherein the carrying out the at least one classification and target recognition of the object comprises at least one of classifying and target recognizing of the object through the detection of the plurality of features.

19. The method according to claim 17, wherein the determining of the feature that represents a part of the object comprises determining a plurality of features.

20. The method according to claim 19, wherein the determining of at least one condition comprises determining at least one condition for each of the plurality of features.

21. The method according to claim 19, wherein the carrying out of the at least one classification and target recognition of the object comprises at least one of classifying and target recognizing of the object through the detection of the plurality of features.

22. The method according to claim 17, wherein a programmable algorithm is associated with the at least one condition and the method further comprises programming the algorithm as desired.

23. The method according to claim 17 further comprising:

preprocessing for the detection of a specific feature;

testing, before the preprocessing for the detection of the specific feature, whether the preprocessing for the detection of the specific feature has been carried out in connection with an other feature; and

using, when preprocessing for the detection of the specific feature has been carried out for the other feature, the preprocessing of the another feature as the preprocessing for the detection of the specific feature.

24. The method according to claim 23 further comprising:

storing the preprocessing in a cache memory.

25. The method according to claim 23, wherein the specific feature is one of a left edge and right edge of an object and the preprocessing of each of these features comprises edge image preprocessing.

26. The method according to claim 23 further comprising:

storing all reusable preprocessing as a sequence of compilation.

27. The method according to claim 24, wherein the cache is not restricted to a type of preprocessing.

28. The method according to claim 17, wherein the object is an aircraft.

29. The method according to claim 17, wherein the object is a helicopter.

30. The method according to claim 17, further comprising:

estimating a change in position of the object in space.

31. A method for model-based classification and target recognition of an object, the method comprising:

recording an image of an inanimate object;

detecting the inanimate object in the image by creating a region of interest (ROI);

determining a feature that represents a recognized part of the inanimate object;

determining at least one condition linked with the feature that indicates an applicability of the feature; and

carrying out object classification and target recognition of the object when the at least one condition indicates the applicability of the feature and when the feature of the object is visible and recordable according to the position of the object with reference to a camera;

matching a position created by a movement of the inanimate object in space to the position of the inanimate object in the image,

wherein the at least one condition comprises one of geometry of the object, distance of the object from a camera, illumination conditions, contrast, speed of the object, height of the object, and relative position of the object to a camera, and

wherein the recording, determining the feature and the at least one condition and the carrying out are implemented on a computer.

32. The method according to claim 31, wherein the object is a helicopter.