EDGE DIVERSITY OBJECT DETECTION

• US 20120114171A1
• Filed: 11/10/2010
• Published: 05/10/2012
• Est. Priority Date: 11/10/2010
• Status: Active Grant

• Current Assignee: Raytheon Company (Rtx Corporation)
• Original Assignee: Raytheon Company (Rtx Corporation)
• Inventors: Newman, Arthur M., Crow, Brandon
• Granted Patent: US 8,553,933 B2
• Time in Patent Office: Days
• US Class Current: 382/103
• CPC Class Codes: G06T 7/44 using image operators, e.g. filters, edge density metrics or local histograms
• CPC Class Codes: G06V 10/25 Determination of region of interest [ROI] or a volume of interest [VOI]
• CPC Class Codes: G06V 10/462 Salient features, e.g. scale invariant feature transforms [SIFT]

Abstract

Methods for detecting objects in an image. The method includes a) receiving magnitude and orientation values for each pixel in an image and b) assigning each pixel to one of a predetermined number of orientation bins based on the orientation value of each pixel. The method also includes c) determining, for a first pixel, a maximum of all the pixel magnitude values for each orientation bin in a predetermined region surrounding the first pixel. The method also includes d) summing the maximum pixel magnitude values for each of the orientation bins in the predetermined region surrounding the first pixel, e) assigning the sum to the first pixel and f) repeating steps c), d) and e) for all the pixels in the image.

Claims

1. A method for detecting objects in an image, comprising:

a) receiving magnitude and orientation values for each pixel in an image;

b) assigning each pixel to one of a predetermined number of orientation bins based on the orientation value of each pixel;

c) determining, for a first pixel, a maximum of all the pixel magnitude values for each orientation bin in a predetermined region surrounding the first pixel;

d) summing the maximum pixel magnitude values for each of the orientation bins in the predetermined region surrounding the first pixel;

e) assigning the sum to the first pixel; and

f) repeating steps c), d) and e) for all the pixels in the image.

2. The method of claim 1, wherein summing the maximum pixel magnitude values for each of the orientation bins in the predetermined region surrounding the first pixel increases the magnitude value of each pixel having multiple edge orientations in the predetermined region surrounding the pixel.

3. The method of claim 1, comprising generating an updated image of the pixels based on the sum for each pixel.

4. The method of claim 3, wherein generating the updated image comprises establishing thresholds for the pixel sums.

5. The method of claim 4, comprising identifying a target region in the updated image nearest an operator aimpoint by performing a connected-components analysis of the updated image based on the thresholds.

6. The method of claim 1, comprising aggregating the image prior to step a) by a function of horizontal ground sample distance of the image.

7. The method of claim 6, wherein aggregating the image prior to step a) comprises increasing the aggregation of the image via a bivariate function of the ground sample distance of the image and solar glint angle of the image.

8. The method of claim 1, comprising aggregating the image prior to step a) by a function of horizontal ground sample distance and solar glint angle of the image.

9. The method of claim 1, wherein the predetermined number of orientation bins is N and angular range of each bin is

10. A system for detecting objects in an image, comprising:

an input module to receive magnitude and orientation values for each pixel in an image; and

an image processing module to;

a) assign each pixel to one of a predetermined number of orientation bins based on the orientation value of each pixel;

b) determine, for a first pixel, a maximum of all the pixel magnitude values for each orientation bin in a predetermined region surrounding the first pixel;

c) sum the maximum pixel magnitude values for each of the orientation bins in the predetermined region surrounding the first pixel;

d) assign the sum to the first pixel; and

e) repeat steps c), d) and e) for all the pixels in the image.

11. The system of claim 10, comprising an image aggregation module to aggregate the image prior to step a) by a function of horizontal ground sample distance of the image, wherein the image aggregation module provides the aggregated image to the pixel processing module.

12. The system of claim 11, wherein the image aggregation module is configured to increase the aggregation of the image via a bivariate function of the ground sample distance of the image and solar glint angle of the image.

13. The system of claim 10, comprising an image aggregation module to aggregate the image prior to step a) by a function of horizontal ground sample distance and solar glint angle of the image, wherein the image aggregation module provides the aggregated image to the pixel processing module.

14. A system for detecting objects in an image, comprising:

a) means for receiving magnitude and orientation values for each pixel in an image;

b) means for assigning each pixel to one of a predetermined number of orientation bins based on the orientation value of each pixel;

c) means for determining, for a first pixel, a maximum of all the pixel magnitude values for each orientation bin in a predetermined region surrounding the first pixel;

d) means for summing the maximum pixel magnitude values for each of the orientation bins in the predetermined region surrounding the first pixel;

e) means for assigning the sum to the first pixel; and

f) means for repeating steps c), d) and e) for all the pixels in the image.

15. A computer program product, tangibly embodied in an information carrier, the computer program product including instructions being operable to cause an image processing module to:

a) receive magnitude and orientation values for each pixel in an image;

b) assign each pixel to one of a predetermined number of orientation bins based on the orientation value of each pixel;

c) determine, for a first pixel, a maximum of all the pixel magnitude values for each orientation bin in a predetermined region surrounding the first pixel;

d) sum the maximum pixel magnitude values for each of the orientation bins in the predetermined region surrounding the first pixel;

e) assign the sum to the first pixel; and

f) repeat steps c), d) and e) for all the pixels in the image.

16. The computer program product of claim 15, wherein the instructions are operable to cause an image aggregation module to aggregate the image prior to step a) by a function of horizontal ground sample distance of the image, wherein the image aggregation module provides the aggregated image to the pixel processing module.

17. The computer program product of claim 16, wherein the instructions are operable to cause an image aggregation module to increase the aggregation of the image via a bivariate function of the ground sample distance of the image and solar glint angle of the image.

18. The computer program product of claim 15, wherein the instructions are operable to cause an image aggregation module to aggregate the image prior to step a) by a function of horizontal ground sample distance and solar glint angle of the image, wherein the image aggregation module provides the aggregated image to the pixel processing module.