Systems and methods for recognizing a target from a moving platform

• US 8,320,615 B2
• Filed: 12/05/2008
• Issued: 11/27/2012
• Est. Priority Date: 02/27/2008
• Status: Active Grant

• Current Assignee: Honeywell International Inc.
• Original Assignee: Honeywell International Inc.
• Inventors: Hamza, Rida M., Mohideen, Mohammed Ibrahim
• Primary Examiner(s): Johns, Andrew W
• Application Number:
  US12/329,276
• Publication Number:
  US 20090214079A1
• Time in Patent Office: 1,453 Days
• Field of Search: 382/103, 382/104, 382/199, 382/217, 382/218, 382/281
• US Class Current: 382/103
• CPC Class Codes: G06T 7/13 Edge detection
• CPC Class Codes: G06T 7/74 involving reference images or patches
• 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 and methods for recognizing a location of a target are provided. One system includes a camera configured to generate first data representing an object resembling the target, a memory storing second data representing a template of the target, and a processor. The processor is configured to receive the first data and the second data, and determine that the object is the target if the object matches the template within a predetermined percentage error. A method includes receiving first data representing an object resembling the target, receiving second data representing a template of the target, and determining that the object is the target if the object matches the template within a predetermined percentage error. Also provided are computer-readable mediums including processor instructions for executing the above method.

Claims

1. A system for recognizing a location of a target including one or more major edges and one or more minor edges, comprising:

a camera configured to generate first data representing an object resembling the target;

a pre-stored database in a memory storing second data representing a template of the target and including edges corresponding to each major edge and each minor edge; and

a processor coupled to the camera and the memory, the processor configured to;

receive the first data and the second data, and

determine that the object is the target if the object matches the template within a predetermined percentage error.

2. The system of claim 1, wherein the processor is further configured to:

rotate the template to line-up the one or more object edges and the set of edges; and

scale a size of the set of edges to a size of the one or more object edges.

3. The system of claim 2, wherein the processor is further configured to use the first data to determine an actual location of the target if the one or more object edges match the set of edges edge within the predetermined percentage error.

4. The system of claim 1, wherein the processor is further configured to:

match a first major edge of the object and a first corresponding major edge of the template; and

match a second major edge of the object and a second corresponding major edge of the template when making the determination.

5. The system of claim 4, wherein the processor is further configured to:

calculate a first slope of the first object major edge and a second slope of the second object major edge;

calculate a first intercept equation for the first slope and a second intercept equation for the second slope;

add a predefined error margin to the first intercept equation and the second intercept equation to define a first range of slopes for the first slope and a second range of slopes for the second slope;

perform a Hough search for a third slope in the first range that matches a fourth slope of the first corresponding major edge; and

perform a Hough search for a fifth slope in the second range that matches a sixth slope of the second corresponding major edge.

6. The system of claim 5, wherein the processor is further configured to:

compare the third slope, the fifth slope, or both to slopes of corresponding edges of the target template; and

determine the percentage error based on the comparison.

7. The system of claim 5, wherein the processor is further configured to:

perform a Dirac line-fitting algorithm on a first edge including the third slope; and

perform a Dirac line-fitting algorithm on a second edge including the fifth slope.

8. The system of claim 7, wherein the processor is further configured to:

compare the third slope, the fifth slope, or both to slopes of corresponding edges of the target template; and

determine the percentage error based on the comparison.

9. The system of claim 8, wherein the processor is further configured to use the first data to determine an actual location of the target if the object is determined to be the target.

10. A method for recognizing a location of a target including one or more major edges and one or more minor edges, the method comprising the steps of:

receiving first data representing an object having edges resembling the target;

receiving second data from a pre-stored navigation database, the second data representing a template of the target and including an edge corresponding to each major edge and minor edge; and

determining that the object is the target if the object edges match the template major edges and minor edges within a predetermined percentage error.

11. The method of claim 10, wherein the determining step comprises the steps of:

rotating the template to line-up object edges and at least one template major edge; and

scaling a size of the template to a size of the object.

12. The method of claim 10, further comprising the step of using the first data to determine an actual location of the target if the object is the target.

13. The method of claim 10, wherein the determining step comprises the steps of:

matching a first major edge of the object and a first corresponding major edge of the template; and

matching a second major edge of the object and a second corresponding major edge of the template when making the determination.

14. The method of claim 10, wherein the determining step comprises the steps of:

calculating a first slope of the first object major edge and a second slope of the second object major edge;

calculating a first intercept equation for the first slope and a second intercept equation for the second slope;

adding a predefined error margin to the first intercept equation and the second intercept equation to define a first range of slopes for the first slope and a second range of slopes for the second slope;

performing a Hough search for a third slope in the first range that matches a fourth slope of the first corresponding major edge; and

performing a Hough search for a fifth slope in the second range that matches a sixth slope of the second corresponding major edge.

15. The method of claim 14, wherein the determining step further comprises the steps of:

comparing the third slope, the fifth slope, or both to slopes of corresponding edges of the target template; and

determining the percentage error based on the comparison.

16. The method of claim 14, wherein the determining step further comprises the steps of:

performing a Dirac line-fitting algorithm on a first edge including the third slope; and

performing a Dirac line-fitting algorithm on a second edge including the fifth slope.

17. The method of claim 16, wherein the determining step further comprises the steps of:

comparing the third slope, the fifth slope, or both to slopes of corresponding edges of the target template;

determining the percentage error based on the comparison; and

using the first data to determine an actual location of the target if the object is determined to be the target.

18. A non-transitory computer-readable medium including instructions that, when executed by a processor, cause the processor to perform a method for recognizing a location of a target including one or more major edges, the method comprising the steps of:

receiving first data representing an object having edges resembling the target;

receiving second data from a pre-stored navigation database, the second data representing a template of the target and including an edge corresponding to each major edge and minor edge; and

determining that the object is the target if the object edges match the template major edges and minor edges within a predetermined percentage error.

19. The non-transitory computer-readable medium of claim 18, further including instructions that cause the processor to perform the steps of:

rotating the template to line-up object edges and at least one template major edge; and

scaling a size of the template to a size of the object.

20. The non-transitory computer-readable medium of claim 18, further including instructions that cause the processor to perform the steps of:

calculating a first slope of the first object edge and a second slope of the second object edge;

calculating a first intercept equation for the first slope and a second intercept equation for the second slope;

adding a predefined error margin to the first intercept equation and the second intercept equation to define a first range of slopes for the first slope and a second range of slopes for the second slope;

performing a Hough search for a third slope in the first range that matches a fourth slope of the first corresponding edge;

performing a Hough search for a fifth slope in the second range that matches a sixth slope of the second corresponding edge;

performing a Dirac line-fitting algorithm on a first edge including the third slope; and

performing a Dirac line-fitting algorithm on a second edge including the fifth slope.