Method and system for image processing for structured light profiling of a part

• US 7,302,109 B2
• Filed: 08/28/2003
• Issued: 11/27/2007
• Est. Priority Date: 08/28/2003
• Status: Expired due to Fees

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Ross, Joseph Benjamin, Harding, Kevin George, Hu, Qingying, Lorraine, Peter William
• Primary Examiner(s): Kassa; Yosef
• Application Number:
  US10/652,366
• Publication Number:
  US 20050046872A1
• Time in Patent Office: 1,552 Days
• Field of Search: 382/260, 382/274, 382/275, 382/282, 382/284, 382/294, 382/302, 358/1.7, 358/3.26, 358/3.27, 358/509, 358/520, 358/537, 358/738
• US Class Current: 382/260
• CPC Class Codes: G01B 11/25 by projecting a pattern, e.g. one or more lines, moiré fringes on the object G01B11/255 takes precedence ; image analysis for depth or shape recovery G06T7/50
• CPC Class Codes: G06T 7/521 from laser ranging, e.g. using interferometry; from the projection of structured light

Abstract

An image processing method for structured light profiling includes sampling an image of a structured light pattern to obtain an intensity distribution, selecting a number of sets of sampled points from the intensity distribution. Each of the respective sets includes a number of sampled points. The image processing method further includes fitting each of the sets of sampled points to a respective distribution function and filtering the distribution functions to select a representative distribution function for the intensity distribution.

Claims

1. An image processing method for structured light profiling, said method comprising:

sampling an image of a structured light pattern to obtain an intensity distribution;

selecting a plurality of sets of sampled points from the intensity distribution, wherein each of the respective sets comprises a plurality of sampled points;

fitting each of the sets of sampled points to a respective Gaussian distribution function; and

filtering the Gaussian distribution functions to select a representative distribution function for the intensity distribution.

2. The image processing method of claim 1, further comprising extracting a center of the representative distribution function.

3. The image processing method of claim 2, wherein said extracting the center comprises using zero-crossing.

4. The image processing method of claim 1, wherein each of the sets of sampled points comprises at least three sampled points.

5. The image processing method of claim 1, wherein each of the distribution functions comprises a Gaussian distribution.

6. The image processing method of claim 1, further comprising extracting a respective center for each of the distribution functions, wherein said filtering includes using the centers.

7. The image processing method of claim 6, wherein said extracting comprises using zero-crossing.

8. The image processing method of claim 6, wherein said filtering includes rejecting a plurality of outliers.

9. The image processing method of claim 6, wherein said filtering includes selecting a median of the centers, wherein the representative distribution function corresponds to the median.

10. The image processing method of claim 9, wherein said filtering further includes using a histogram to determine the median.

11. The image processing method of claim 9, wherein said filtering further includes sorting the centers to determine the median.

12. The image processing method of claim 1, wherein said structured light pattern comprises at least one laser stripe, and wherein said intensity distribution is an intensity profile across one of the laser stripes.

13. The image processing method of claim 1, further comprising acquiring the image of the structured light pattern of a part.

14. The image processing method of claim 13, further comprising reconstructing a three dimensional profile of the part, using the representative distribution function.

15. An image processing method for structured light profiling, said method comprising:

sampling an image of a structured light pattern to obtain an intensity distribution;

selecting a plurality of sets of sampled points from the intensity distribution, wherein each of the sets comprises at least three sampled points;

fitting each of the sets of sampled points to respective Gaussian distribution functions;

extracting a center for each of the Gaussian distribution functions;

filtering the Gaussian distribution functions by using the centers to select a representative distribution function for the intensity distribution.

16. The image processing method of claim 15, wherein said extracting comprises using zero-crossing.

17. The image processing method of claim 15, wherein said filtering includes selecting a median of the centers, wherein the representative distribution function corresponds to the median.

18. An image processing method for reconstructing a three dimensional profile of a part, said method comprising:

projecting at least one laser beam on the part;

acquiring an image of a structured light pattern of the part;

sampling the image to obtain an intensity distribution;

selecting a plurality of sets of sampled points from the intensity distribution, wherein each of the sets comprises at least three sampled points;

fitting each of the sets of sampled points to a respective Gaussian distribution function;

extracting a center for each of the Gaussian distribution functions;

filtering the Gaussian distribution functions by using the centers to select a representative distribution function for the intensity distribution; and

using the representative distribution function for the intensity distribution to generate the three dimensional profile of the part.

19. The image processing method of claim 18, wherein said filtering includes selecting a median of the centers, wherein the representative distribution function corresponds to the median.

20. A system for obtaining a three dimensional profile of a part using a structured light pattern, said system comprising:

a source of structured light positioned at a predetermined distance from a part, wherein the source projects a beam of structured light to illuminate the part;

at least one imaging device configured to acquire an image of a structured light pattern of the part, wherein the at least one imaging device is positioned such that an angle of view of the imaging device is different from an angle of illumination of the source; and

a processor coupled to the at least one imaging device, wherein the processor is configured for

sampling the image of a structured light pattern to obtain an intensity distribution;

selecting a plurality of sets of sampled points from the intensity distribution, and wherein each of the sets comprises at least three sampled points;

fitting each of the sets of sampled points to respective Gaussian distribution functions;

extracting a center for each of the Gaussian distribution functions;

filtering the Gaussian distribution functions by using the centers to select a representative distribution function for the intensity distribution; and

reconstructing a three dimensional profile of the part, using the representative distribution function.

21. The system of claim 20, wherein said processor is further configured for selecting a median of the respective centers, wherein the representative distribution function corresponds to the median.

22. A computer readable medium for storing and/or transmitting instructions that, when executed by a computer, perform a method for image processing for structured light profiling, said method comprising:

sampling an image of a structured light pattern to obtain an intensity distribution;

selecting a plurality of sets of sampled points from the intensity distribution, wherein each of the sets comprises a plurality of sampled points;

fitting each of the sets of sampled points to a respective distribution function; and

filtering the distribution functions to select a representative distribution function for the intensity distribution.

23. The computer readable medium of claim 22, wherein each of the sets of sampled points comprises at least three sampled points.

24. The computer readable medium of claim 22, wherein each of the distribution functions comprises a Gaussian distribution.

25. The computer readable medium of claim 22, wherein the method further includes extracting a respective center for each of the distribution functions, wherein said filtering includes using the centers.

26. The computer readable medium of claim 25, wherein the extracting comprises using zero-crossing.

27. The computer readable medium of claim 25, wherein the filtering includes selecting a median of the centers, wherein the representative distribution function corresponds to the median.