Method and apparatus for witness card statistical analysis using image processing techniques

• US 7,277,570 B2
• Filed: 02/17/2004
• Issued: 10/02/2007
• Est. Priority Date: 09/15/2003
• Status: Active Grant

• Current Assignee: Peraton, Inc.
• Original Assignee: ITT Manufacturing Enterprises, Inc. (ITT, Inc.)
• Inventors: Armstrong, Wayne
• Primary Examiner(s): CHAWAN, SHEELA C
• Application Number:
  US10/778,085
• Publication Number:
  US 20050058334A1
• Time in Patent Office: 1,323 Days
• Field of Search: 382/141, 382/103, 250/288, 250/423.P, 366/132, 366/160.2, 366/348, 118/679, 118/680, 118/683, 118/688, 118/692, 118/666, 427/8, 427/424, 427/427.5, 427/426, 427/427.2, 427/207.1, 427/427, 510/278, 510/302, 510/470, 510/530, 510/224, 510/446, 106/287.25, 106/287.26, 106/287.23
• US Class Current: 382/141
• CPC Class Codes: A01M 7/0096 Testing of spray-patterns
• CPC Class Codes: G01N 15/1433 using image recognition

Abstract

A method and apparatus for performing witness card statistical analysis using image processing techniques to quickly and efficiently generate as-sprayed performance statistics for a spray device, or spray, based upon a comprehensive analysis of as-sprayed witness card stains. Calibration and as-sprayed witness cards are scanned to produce images that are processed using image processing techniques to identify stain areas/dimensions. Calibration stain data is associated with known calibration droplet volumes and used to generate a set of calibration equations that model an observed relationship between the area of calibration stains upon a witness card and the volume of the respective fluid droplets that produced the stains. As-sprayed stain area/dimension information is processed using the developed calibration equations to approximate the volume of as-sprayed droplets. The approach provides a direct quantitative assessment of spray device performance based upon a comprehensive assessment of as-sprayed witness cards, resulting in highly accurate, timely spray device performance statistics.

Claims

1. A system for assessing a spray using image processing techniques to analyze a scan image of an as-sprayed witness card, wherein the as-sprayed witness card includes a fixed pattern of stains as a result of being sprayed with drops of a selected fluid, the system comprising:

a scanner unit to generate a scan image of a calibration witness card and a scan image of at least one as-sprayed witness card, wherein the calibration witness card includes a plurality of stains, each stain created with a known volume of the selected fluid;

an image analysis unit to identify a plurality of stains within a scan image and to determine a value for a selected dimensional characteristic for each identified stain based upon image processing of the scan image;

a calibration unit to develop a calibration equation based upon values determined for stains identified within the calibration witness card scan image, wherein the calibration equation approximates a relationship between the determined calibration witness card stain values and the respective volumes of the selected fluid that created each respective calibration witness card stain; and

a statistics unit to determine an as-sprayed drop characteristic based upon a value determined for a stain identified within the as-sprayed witness card scan image and the developed calibration equation.

2. The system of claim 1, wherein the calibration equation includes a non-linear component.

3. The system of claim 1, wherein the calibration equation includes a set of calibration equations.

4. The system of claim 3, wherein the set of calibration equations includes at least one non-linear equation.

5. The system of claim 1, wherein the scanner unit further includes:

a scan color bias unit to increase the sensitivity of the scanner to at least one selected color.

6. The system of claim 1, wherein the scanner unit further includes:

an image storage unit that stores a generated scan image.

7. The system of claim 6, wherein the image storage unit is configured to store the scan image as a gray scale image.

8. The system of claim 6, wherein the image storage unit is configured to store the scan image as a color image.

9. The system of claim 6, wherein the image storage unit is configured to store the scan image in one of a file and a database.

10. The system of claim 1, wherein the dimensional characteristic value determined by the image analysis unit for a stain is at least one of:

an area of an identified stain;

a diameter of an identified stain;

a radius of an identified stain; and

a circumference of an identified stain.

11. The system of claim 1, wherein the image analysis unit further includes:

a value storage unit to store determined witness card stain values.

12. The system of claim 11, wherein the value storage unit is configured to store values in at least one of a file and a database.

13. The system of claim 1, wherein the calibration unit further includes:

an equation storage unit to store at least one of a determined equation and a determined equation coefficient.

14. The system of claim 13, wherein the equation storage unit is configured to store determined equations in at least one of a file and a database.

15. The system of claim 1, wherein the as-sprayed characteristic determined by the statistics unit is at least one of:

an as-sprayed drop diameter;

an as-sprayed drop volume;

an as-sprayed drop mass;

an as-sprayed drop mass median diameter; and

an as-sprayed spray density.

16. A method for assessing a spray using image processing techniques to analyze a scan image of an as-sprayed witness card, wherein the as-sprayed witness card includes a fixed pattern of stains as a result of being sprayed with drops of a selected fluid, the method comprising:

(a) generating a scan image of a calibration witness card and a scan image of at least one as-sprayed witness card, wherein the calibration witness card includes a plurality of stains, each stain created with a known volume of the selected fluid;

(b) identifying a plurality of stains within a scan image and determining a value for a selected dimensional characteristic for each identified stain based upon image processing of the scan image;

(c) determining a calibration equation based upon values determined for stains identified within the calibration witness card scan image, wherein the calibration equation approximates a relationship between the determined calibration witness card stain values and the respective volumes of the selected fluid that created each respective calibration witness card stain; and

(d) determining an as-sprayed drop characteristic based upon a value determined for a stain identified within the as-sprayed witness card scan image and the developed calibration equation.

17. The method of claim 16, wherein the calibration equation includes a non-linear component.

18. The method of claim 16, wherein the calibration equation includes a set of calibration equations.

19. The method of claim 18, wherein the set of calibration equations includes at least one non-linear equation.

20. The method of claim 16, wherein step (a) further includes:

(a.1) increasing the sensitivity of the scanner to at least one selected color.

21. The method of claim 16, wherein step (a) further includes:

(a.1) storing a generated scan image.

22. The method of claim 21, wherein step (a.1) further includes:

(a.1.1) storing a generated scan image as a gray scale image.

23. The method of claim 21, wherein step (a.1) further includes:

(a.1.1) storing a generated scan image as a color image.

24. The method of claim 21, wherein step (a.1) further includes:

(a.1.1) storing a generated scan image in one of a file and a database.

25. The method of claim 16, wherein the determined dimensional characteristic is at least one of:

an area of an identified stain;

a diameter of an identified stain;

a radius of an identified stain; and

a circumference of an identified stain.

26. The method of claim 16, wherein step (b) further includes:

(b.1) storing a determined witness card stain value.

27. The method of claim 26, wherein step (b.1) further includes:

(b.1.1) storing a determined witness card stain value in at least one of a file and a database.

28. The method of claim 16, wherein step (c) further includes:

(c.1) storing at least one of a determined equation and a determined equation coefficient.

29. The method of claim 28, wherein step (c.1) further includes:

(c.1.1) storing at least one of the determined equation and a determined equation coefficient in at least one of a file and a database.

30. The method of claim 16, wherein step (d) the determined as-sprayed characteristic is at least one of:

an as-sprayed drop diameter;

an as-sprayed drop volume;

an as-sprayed drop mass;

an as-sprayed drop mass median diameter; and

an as-sprayed spray density.

31. A program product apparatus having a computer readable medium with computer program logic recorded thereon for assessing a spray using image processing techniques to analyze a scan image of an as-sprayed witness card, wherein the as-sprayed witness card includes a fixed pattern of stains as a result of being sprayed with drops of a selected fluid, said program product apparatus comprising:

a scanner unit to generate a scan image of a calibration witness card and a scan image of at least one as-sprayed witness card, wherein the calibration witness card includes a plurality of stains, each stain created with a known volume of the selected fluid;

an image analysis unit to identify a plurality of stains within a scan image and to determine a value for a selected dimensional characteristic for each identified stain based upon image processing of the scan image;

a calibration unit to develop a calibration equation based upon values determined for stains identified within the calibration witness card scan image, wherein the calibration equation approximates a relationship between the determined calibration witness card stain values and the respective volumes of the selected fluid that created each respective calibration witness card stain; and

a statistics unit to determine an as-sprayed drop characteristic based upon a value determined for a stain identified within the as-sprayed witness card scan image and the developed calibration equation.

32. The program product of claim 31, wherein the calibration equation includes a non-linear component.

33. The program product of claim 31, wherein the calibration equation includes a set of calibration equations.

34. The program product of claim 33, wherein the set of calibration equations includes at least one non-linear equation.

35. The program product of claim 31, wherein the scanner unit further includes:

a scan color bias unit to increase the sensitivity of the scanner to at least one selected color.

36. The program product of claim 31, wherein the scanner unit further includes:

an image storage unit that stores a generated scan image.

37. The program product of claim 36, wherein the image storage unit is configured to store the scan image as a gray scale image.

38. The program product of claim 36, wherein the image storage unit is configured to store the scan image as a color image.

39. The program product of claim 36, wherein the image storage unit is configured to store the scan image in one of a file and a database.

40. The program product of claim 31, wherein the dimensional characteristic value determined by the image analysis unit for a stain is at least one of:

an area of an identified stain;

a diameter of an identified stain;

a radius of an identified stain; and

a circumference of an identified stain.

41. The program product of claim 31, wherein the image analysis unit further includes:

a value storage unit to store determined witness card stain values.

42. The program product of claim 41, wherein the value storage unit is configured to store values in at least one of a file and a database.

43. The program product of claim 31, wherein the calibration unit further includes:

an equation storage unit to store at least one of a determined equation and a determine equation coefficient.

44. The program product of claim 43, wherein the equation storage unit is configured to store determined equations in at least one of a file and a database.

45. The program product of claim 31, wherein the as-sprayed characteristic determined by the statistics unit is at least one of:

an as-sprayed drop diameter;

an as-sprayed drop volume;

an as-sprayed drop mass;

an as-sprayed drop mass median diameter; and

an as-sprayed spray density.

46. A method for calibrating a system for assessing a spray using image processing techniques to analyze a scan image of an as-sprayed witness card, wherein the as-sprayed witness card includes a fixed pattern of stains as a result of being sprayed with drops of a selected fluid, the method comprising:

(a) generating a scan image of a calibration witness card, wherein the calibration witness card includes a plurality of stains, each stain created with a known volume of the selected fluid;

(b) identifying a plurality of stains within the scan image and determining a value for a selected dimensional characteristic for each identified stain based upon image processing of the scan image; and

(c) determining a calibration equation based upon values determined for stains identified within the calibration witness card scan image, wherein the calibration equation approximates a relationship between the determined calibration witness card stain values and the respective volumes of the selected fluid that created each respective calibration witness card stain;

wherein the calibration equation is used for determining an as-sprayed drop characteristic based upon a value determined for a stain identified within the as-sprayed witness card scan image and the developed calibration equation.

47. The method of claim 46, wherein the calibration equation includes a non-linear component.

48. The method of claim 46, wherein the calibration equation includes a set of calibration equations.

49. The method of claim 48, wherein the set of calibration equations includes at least one non-linear equation.

50. The method of claim 46, wherein step (a) further includes:

(a.1) increasing the sensitivity of the scanner to at least one selected color.

51. The method of claim 46, wherein step (a) further includes:

(a.1) storing a generated scan image.

52. The method of claim 51, wherein step (a.1) further includes:

(a.1.1) storing a generated scan image as a gray scale image.

53. The method of claim 51, wherein step (a.1) further includes:

(a.1.1) storing a generated scan image as a color image.

54. The method of claim 51, wherein step (a.1) further includes:

(a.1.1) storing a generated scan image in one of a file and a database.

55. The method of claim 46, wherein the determined dimensional characteristic is at least one of:

an area of an identified stain;

a diameter of an identified stain;

a radius of an identified stain; and

a circumference of an identified stain.

56. The method of claim 46, wherein step (b) further includes:

(b.1) storing a determined witness card stain value.

57. The method of claim 56, wherein step (b.1) further includes:

(b.1.1) storing a determined witness card stain value in at least one of a file and a database.

58. The method of claim 46, wherein step (c) further includes:

(c.1) storing at least one of a determined equation and a determined equation coefficient.

59. The method of claim 58, wherein step (c.1) further includes:

(c.1.1) storing at least one of the determined equation and a determined equation coefficient in at least one of a file and a database.

60. The method of claim 46, wherein step (d) the determined as-sprayed characteristic is at least one of:

an as-sprayed drop diameter;

an as-sprayed drop volume;

an as-sprayed drop mass;

an as-sprayed drop mass median diameter; and

an as-sprayed spray density.