Pattern matching system utilizing discrete curve matching with a mapping operator

• US 7,171,048 B2
• Filed: 10/03/2002
• Issued: 01/30/2007
• Est. Priority Date: 04/10/2002
• Status: Active Grant

• Current Assignee: National Instruments Corporation (Emerson Electric Company)
• Original Assignee: National Instruments Corporation (Emerson Electric Company)
• Inventors: Nair, Dinesh, Wenzel, Lothar, Schmidt, Darren R., Crotty, Kevin M., Rajagopal, Ram, Kumar, Satish V., Fisher, Matthew S.
• Primary Examiner(s): Mancuso; Joseph
• Assistant Examiner(s): Tarcu; Robert
• Application Number:
  US10/263,560
• Publication Number:
  US 20030198388A1
• Time in Patent Office: 1,580 Days
• Field of Search: 382/281
• US Class Current: 382/209
• CPC Class Codes: G06V 10/7515 Shifting the patterns to accommodate for positional errors
• CPC Class Codes: G06V 10/752 Contour matching

Abstract

System and method for determining the presence of an object of interest in a target data set. Portions of a target data set may be located that match an object of interest, e.g., in a template data set, with respect to various information, e.g., edge or boundary information. The invention includes improved methods for mapping point sets or curves to new point sets or curves for curve matching. The method determines the presence of an object of interest in a target data set despite of or using various types of topological transformations of the object of interest in the target data set. One or more mapping operators are determined based on template curves and/or example target curves. Pattern matching is performed on one or more target data sets using the mapping operator(s) to generate pattern matching results, and the pattern matching results output.

Claims

1. A method for performing curve matching between a target discrete curve and a template discrete curve, the method comprising:

acquiring a target data set;

determining a target discrete curve from the target data set, wherein the target discrete curve corresponds to a respective object in the target data set;

analyzing one or more example target data sets to determine one or more example target discrete curves, wherein each of the one or more example target discrete curves corresponds to a data object or part of a data object in the one or more example target data sets;

characterizing an object of interest to produce a mapped template discrete curve, wherein said characterizing the object of interest comprises;

determining a template discrete curve from information regarding the object of interest, wherein the template discrete curve corresponds to the object of interest;

determining the mapping operator based on the determined template discrete curve and the one or more example target discrete curves;

mapping the template discrete curve that corresponds to the object of interest to the mapped template discrete curve using the mapping operator;

performing curve matching on the target discrete curve and the mapped template discrete curve, wherein said performing curve matching computes a distance for the target discrete curve relative to the mapped template discrete curve, and wherein said performing curve matching on the target discrete curve and the mapped template discrete curve comprises determining whether the respective object in the target data set corresponds to the object of interest; and

generating curve matching results based on the distances.

2. The method of claim 1,

wherein said determining the target discrete curve from the target data set comprises performing boundary detection on the target data set to determine boundaries of objects present in the target data set.

3. The method of claim 1,

wherein said determining a target discrete curve from the target data set comprises:

detecting at least one boundary present in the target data set, wherein the at least one boundary corresponds to a shape of an object in the target data set; and

determining the target discrete curve from the at least one boundary.

4. The method of claim 1,

wherein said determining a target discrete curve from the target data set comprises normalizing the target discrete curve.

5. The method of claim 4,

wherein said normalizing comprises normalizing one or more of:

energy of the target discrete curve; and

length of the target discrete curve.

6. The method of claim 1,

wherein said determining a target discrete curve from the target data set comprises re-sampling the target discrete curve;

and

wherein, after said re-sampling, the target discrete curve and the mapped template discrete curve have the same number of points.

7. The method of claim 1,

wherein said determining the target discrete curve from the target data set comprises:

determining an initial target discrete curve from the target data set; and

mapping the initial target discrete curve to a mapped target discrete curve using the mapping operator, wherein the mapped target discrete curve comprises the target discrete curve; and

wherein said performing curve matching on the target discrete curve and the mapped template discrete curve comprises performing curve matching on the mapped target discrete curve and the mapped template discrete curve.

8. The method of claim 1,

wherein said generating curve matching results comprises generating information indicating one or wore matches for an object of interest in the target data set.

9. The method of claim 1,

wherein said determining comprises determining a plurality of target discrete curves from the target data set, wherein each of the plurality of target discrete curves corresponds to a respective data set object in the target data set;

wherein said performing curve matching comprises performing curve matching on each of the target discrete curves relative to the mapped template discrete curve, wherein said performing curve matching computes a distance measure for each of the target discrete curves relative to the mapped template discrete curve; and

wherein said generating curve matching results comprises generating curve matching results based on the distance measures for each of the target discrete curves.

10. The method of claim 9,

wherein said performing curve matching comprises performing curve matching on each of die target discrete curves relative to each of a plurality of mapped template discrete curves, wherein said performing curve matching computes a distance measure for each of the target discrete curves relative to each of the mapped template discrete curves;

and

wherein said generating curve matching results comprises generating curve matching results based on the distance measures for each of the target discrete curves.

11. The method of claim 1,

wherein the discrete curves comprise sequences of points.

12. The method of claim 11,

wherein the target data set is interpretable as a complex plane;

wherein the discrete curves comprise sequences of points; and

wherein positions of said points comprise complex values.

13. The method of claim 1, wherein said characterizing the object of interest is performed prior to said acquiring the target data set.

14. The method of claim 1,

wherein the information regarding the object of interest comprises a template data set containing the object of interest.

15. The method of claim 1, wherein said determining the mapping operator comprises:

normalizing the template discrete curve and the one or more example target discrete curves; and

computing a weight vector W_m, such that

${\langle <br><br>c_n,<br><br>c_m\rangle <br><br>}_{w_m}=\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br><br><br>c_{\mathrm{ni}}<br><br>c_{\mathrm{mi}}^{*}<br><br>W_{\mathrm{mi}}={\mathrm{\delta <br><br>}}_{\mathrm{nm}}$

wherein C_m comprises the normalized template discrete curve and wherein C_n comprises any one of the one or more example target discrete curves; and

wherein δ

_nm is the Kronecker delta.

16. The method of claim 1, further comprising:

analyzing the mapped template discrete curve and one or more example target discrete curves generated from one or more example target data sets to determine at least one parameter for the mapping operator; and

configuring the mapping operator according to the determined at least one parameter.

17. The method of claim 16,

wherein the at least one parameter is used to increase a distance between mapped discrete curves corresponding to the object of interest and mapped discrete curves corresponding to objects that are not of interest.

18. The method of claim 1,

wherein the distance between the target discrete curve and the mapped template discrete curve is greater tan a distance computed between the target discrete curve and the template discrete curve.

19. The method of claim 1,

wherein the target discrete curve characterizes one or more discrete curves;

and

wherein the mapped template discrete curve characterizes one or more discrete curves.

20. The method of claim 1,

wherein the template discrete curve characterizes a first shape;

and

wherein the mapped template discrete curve characterizes a second shape.

21. The method of claim 1,

wherein said mapping the template discrete curve to the mapped template discrete curve comprises:

applying said mapping operator to each point in the template discrete curve to generate corresponding points in the mapped template discrete curve.

22. The method of claim 1,

wherein the mapping operator is used to enhance a distance between mapped discrete curves corresponding to an object of interest and mapped discrete curves corresponding to objects that are not of interest.

23. The method of claim 1, further comprising:

receiving first information regarding the object of interest;

receiving second information regarding one or more objects that are not of interest;

wherein said determining the mapping operator based on the determined template discrete curve and the one or more example target discrete curves comprises;

determining at least one parameter for the mapping operator based on the first information and the second information, wherein the at least one parameter is determined to enhance a distance between mapped discrete curves corresponding to an object of interest and mapped discrete curves corresponding to the one or more objects that are not of interest; and

configuring the mapping operator according to the determined at least one parameter.

24. The method of claim 1,

wherein the mapping operator is a weighting operator.

25. The method of claim 1,

wherein the mapping operator operates to emphasize differences between respective objects corresponding to respective discrete curves.

26. The method of claim 1,

wherein, the mapped template discrete curve is a unique discrete curve generated from the template discrete curve.

27. The method of claim 1,

wherein the mapped template discrete curve is more stable to data disturbances than the template discrete curve.

28. The method of claim 1,

wherein the mapping operator includes one or more terms that are computable for different objects of interest.

29. The method of claim 1,

wherein the mapping operator includes one or more terms that are computable to enhance differences between respective objects of interest and objects not of interest.

30. The method of claim 1,

wherein the mapping operator comprises a weight vector w;

wherein the template discrete curve comprises a first vector;

wherein said weight vector w, and said first vector have the same number of elements; and

wherein said mapping the template discrete curve to the mapped template discrete curve comprises;

multiplying each element of the weight vector w with corresponding elements in the first vector to generate a second vector, wherein elements of the second vector comprise the mapped template discrete curve.

31. The method of claim 1, further comprising:

outputting said curve matching results.

32. A method for matching discrete curves, the method comprising:

acquiring a target data set;

determining a plurality of target discrete curves from the target data set, wherein each target discrete curve corresponds to a respective object in the target data set;

analyzing one or mare example target data sets to determine one or more example target discrete curves, wherein each of the one or more example target discrete curves corresponds to a data object or part of a data object in the one or more example target data sets;

characterizing an object of interest to produce a mapped template discrete curve, wherein said characterizing the object of interest comprises;

determining a template discrete curve from information regarding the object of interest, wherein the template discrete curve corresponds to the object of interest;

determining the mapping operator based on the determined template discrete curve and the one or more example target discrete curves;

mapping the template discrete curve to the mapped template discrete curve using the mapping operator, wherein the mapped template discrete curve corresponds to the object of interest;

for each of the plurality of target discrete curves, performing curve matching on each of the target discrete curves and the mapped template discrete curve, wherein said performing curve matching computes a distance for the each of the mapped target discrete curves relative to the mapped template discrete curve, and wherein said performing curve matching on the target discrete curve and the mapped template discrete curve comprises determining whether the respective object in the target data set corresponds to the object of interest; and

generating curve matching results based on the distances.

33. The method of claim 32,

wherein said determining the plurality of target discrete curves from the target data set comprises:

determining a plurality of initial target discrete curves from the target data set; and

mapping the plurality of initial target discrete curves to a respective plurality of mapped target discrete curves using the mapping operator, wherein the plurality of mapped target discrete curves comprises the plurality of target discrete curves; and

wherein said performing curve matching on each of the target discrete curves and the mapped template discrete curve comprises performing curve matching on each of the mapped target discrete curve and the mapped template discrete curve.

34. The method of claim 32, further comprising:

acquiring a target data set; and

determining one or more target discrete curves from the target data set, wherein the one or more target discrete curves represents a data object in the target data set.

35. The method of claim 34, further comprising:

wherein said determining the one or more target image discrete curves from the target image comprises;

determining one or more initial target image discrete curves from the target image; and

mapping the one or more initial target image discrete curves to a respective one or more mapped target image discrete curves using the respective mapping operators, wherein the one or more mapped target image discrete curves comprises the one or more target image discrete curves; and

wherein said performing curve matching between the one or more target image discrete curves and the one or more mapped template image discrete curve comprises performing curve matching between each of the one or more mapped target image discrete curves and die one or more mapped template image discrete curves.

36. A computer readable memory medium which stores program instructions for performing curve matching between a target discrete curve and a template discrete curve, wherein the program instructions are executable to perform:

acquiring a target data set;

determining a target discrete curve from the target data set wherein the target discrete curve corresponds to a respective object in the target data set;

analyzing one or more example target data sets to determine one or more example target discrete curves, wherein each of the one or more example target discrete curves corresponds to a data object or part of a data object in the one or more example target data sets,

characterizing an object of interest to produce a mapped template discrete curve, wherein said characterizing the object of interest comprises;

determining a template discrete curve from information regarding the object of interest, wherein the template discrete curve corresponds to the object of interest;

determining the mapping operator based on the determined template discrete curve and the one or more example target discrete curves;

mapping the template discrete curve that corresponds to the object of interest to the mapped template discrete curve using the mapping operator;

performing curve matching on the target discrete curve and the mapped template discrete curve, wherein said performing curve matching computes a distance for the target discrete curve relative to the mapped template discrete curve, and wherein said performing curve matching on the target discrete curve and the mapped template discrete curve comprises determining whether the respective object in the target data set corresponds to the object of interest; and

generating curve matching results based on the distances.

37. The computer readable memory medium of claim 36,

wherein said determining the target discrete curve from the target data set comprises performing boundary detection on the target data set to determine boundaries of objects present in the target data set.

38. The computer readable memory medium of claim 36,

wherein said determining a target discrete curve from the target data set comprises:

detecting at least one boundary present in the target data set, wherein the at least one boundary corresponds to a shape of an object in the target data set; and

determining the target discrete curve from the at least one boundary.

39. The computer readable memory medium of claim 36,

wherein said determining a target discrete curve from the target data set comprises normalizing the target discrete curve.

40. The computer readable memory medium of claim 39,

wherein said normalizing comprises normalizing one or more of:

energy of the target discrete curve; and

length of the target discrete curve.

41. The computer readable memory medium of claim 36,

wherein said determining a target discrete curve from the target data set comprises re-sampling the target discrete curve;

and

wherein, after said re-sampling, the target discrete curve and the mapped template discrete curve have the same number of points.

42. The computer readable memory medium of claim 36,

wherein said determining the target discrete curve from the target data set comprises:

determining an initial target discrete curve from the target data set; and

mapping the initial target discrete curve to a mapped target discrete curve using the mapping operator, wherein the mapped target discrete curve comprises the target discrete curve; and

wherein said performing curve matching on the target discrete curve and the mapped template discrete curve comprises performing curve matching on the mapped target discrete curve and the mapped template discrete curve.

43. The computer readable memory medium of claim 36,

wherein said generating curve matching results comprises generating information indicating one or more matches for an abject of interest in the target data set.

44. The computer readable memory medium of claim 36,

wherein, said determining comprises determining a plurality of target discrete curves from the target data set, wherein each of the plurality of target discrete curves corresponds to a respective data set object in the target data set;

wherein said performing curve matching comprises performing curve matching on each of the target discrete curves relative to the mapped template discrete curve, wherein said performing curve matching computes a distance measure for each of the target discrete curves relative to the mapped template discrete curve; and

wherein said generating curve matching results comprises generating curve matching results based on the distance measures for each of the target discrete curves.

45. The computer readable memory medium of claim 44,

wherein said performing curve matching comprises performing curve matching on each of the target discrete curve relative to each of a plurality of mapped template discrete curves, wherein said performing curve matching computes a distance measure for each of the target discrete curves relative to each of the mapped template discrete curves;

and

wherein said generating curve matching results comprises generating curve matching results based on the distance measures for each of the target discrete curves.

46. The computer readable memory medium of claim 36,

wherein the discrete curves comprise sequences of points.

47. The computer readable memory medium of claim 36,

wherein the target data set is interpretable as a complex plane;

wherein the discrete curves comprise sequences of points; and

wherein positions of said points comprise complex values.

48. The computer readable memory medium of claim 36, wherein said characterizing the object of interest is performed prior to said acquiring the target data set.

49. The computer readable memory medium of claim 36,

wherein the information regarding the object of interest comprises a template data set containing the object of interest.

50. The computer readable memory medium of claim 36, wherein said determining the mapping operator comprises:

normalizing the template discrete curve and the one or more example target discrete curves; and

computing a weight vector W, such that

${\langle <br><br>c_n,<br><br>c_m\rangle <br><br>}_{W_m}=\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br><br><br>c_{\mathrm{ni}}<br><br>c_{\mathrm{mi}}^{*}<br><br>W_i={\mathrm{\delta <br><br>}}_{\mathrm{nm}}$

wherein C_m comprises the normalized template discrete curve and wherein C_n comprises any one of the one or more example target discrete curves; and

wherein δ

_nm is the Kronecker delta.

51. The computer readable memory medium of claim 36, wherein the program instructions are further executable to perform:

analyzing the mapped template discrete curve and one or more example target discrete curves generated from one or more example target data sets to determine at least one parameter for the mapping operator; and

configuring the mapping operator according to the determined at least one parameter.

52. The computer readable memory medium of claim 51,

wherein the at least one parameter is used to increase a distance between mapped sequences corresponding to the object of interest and mapped discrete curves corresponding to objects that are not of interest.

53. The computer readable memory medium of claim 36,

wherein the distance between the mapped target discrete curve and the mapped template discrete curve is greater than a distance computed between the target discrete curve and the template discrete curve.

54. The computer readable memory medium of claim 36,

wherein the target discrete curve characterizes one or more discrete curves;

and

wherein the mapped template discrete curve characterizes one or more discrete curves.

55. The computer readable memory medium of claim 36,

wherein the template discrete curve characterizes a first shape;

and

wherein the mapped template discrete curve characterizes a second shape.

56. The computer readable memory medium of claim 36,

wherein said mapping the template discrete curve to the mapped template discrete curve comprises:

applying said mapping operator to each point in the template discrete curve to generate corresponding points in the mapped template discrete curve.

57. The computer readable memory medium of claim 36,

wherein the mapping operator is used to enhance a distance between mapped discrete curves corresponding to an object of interest and mapped discrete curves corresponding to objects that are not of interest.

58. The computer readable memory medium of claim 36, wherein the program instructions are further executable to perform:

receiving first information regarding an object of interest;

receiving second information regarding one or more objects that are not of interest;

determining at least one parameter for the mapping operator based on the first information and the second information, wherein the at least one parameter is determined to enhance a distance between mapped discrete curves corresponding to an object of interest and mapped discrete curves corresponding to the one or more objects that are not of interest; and

configuring the mapping operator according to the determined at least one parameter.

59. The computer readable memory medium of claim 36,

wherein the mapping operator is a weighting operator.

60. The computer readable memory medium of claim 36,

wherein the mapping operator operates to emphasize differences between respective objects corresponding to respective discrete curves.

61. The computer readable memory medium of claim 36,

wherein the mapped template discrete curve is a unique discrete curve generated from the template discrete curve.

62. The computer readable memory medium of claim 36,

wherein the mapped template discrete curve is more stable to data disturbances than the template discrete curve.

63. The computer readable memory medium of claim 36,

wherein the mapping operator includes one or more terms that are computable for different objects of interest.

64. The computer readable memory medium of claim 36,

wherein the mapping operator includes one or more terms that are computable to enhance differences between respective objects of interest and objects not of interest.

65. The computer readable memory medium of claim 36,

wherein the mapping operator comprises a weight vector W;

wherein the template discrete curve comprises a first vector;

wherein said weight vector W, and said first vector have the same number of elements; and

wherein said mapping the template discrete curve to the mapped template discrete curve comprises;

multiplying each element of the weight vector W with corresponding elements in the first vector to generate a second vector, wherein elements of the second vector comprise the mapped template discrete curve.

66. The computer readable memory medium of claim 36, wherein the program instructions are further executable to perform:

outputting said curve matching results.

67. A computer readable memory medium which stores program instructions for performing curve matching between target discrete curves and a template discrete curve, wherein the program instructions are executable to perform:

acquiring a target data set;

determining a plurality of target discrete curves from the target data set, wherein each target discrete curve corresponds to a respective object in the target data set;

analyzing one or more example target data sets to determine one or more example target discrete curves, wherein each of the one or more example target discrete curves corresponds to a data object or part of a data object in the one or more example target data sets;

characterizing an object of interest to produce a mapped template discrete curve, wherein, said characterizing the object of interest comprises;

determining a template discrete curve from information regarding the object of interest, wherein the template discrete curve corresponds to the object of

determining the mapping operator based on the determined template discrete curve and the one or more example target discrete curves;

mapping the template discrete curve to the mapped template discrete curve using the mapping operator, wherein the mapped template discrete curve corresponds to the object of interest;

for each of the plurality of target discrete curves, performing curve matching on each of the target discrete curves and the mapped template discrete curve, wherein said performing curve matching computes a distance for the each of the mapped target discrete curves relative to the mapped template discrete curve, and wherein said performing curve matching on the target discrete curve and the mapped template discrete curve comprises determining whether the respective object in the target data set corresponds to the object of interest; and

generating curve matching results based on the distances.

68. The computer readable memory medium of claim 67,

wherein said determining the plurality of target discrete curves from the target data set comprises:

determining a plurality of initial target discrete curves from the target data set; and

mapping the plurality of initial target discrete curves to a respective plurality of mapped target discrete curves using the mapping operator, wherein the plurality of mapped target discrete curves comprises the plurality of target discrete curves; and

wherein said performing curve matching on each of the target discrete curves and the mapped template discrete curve comprises performing curve matching on each of the mapped target discrete curve and the mapped template discrete curve.

69. A system for matching discrete curves, the system comprising:

a computer system, comprising;

a processor; and

a memory medium coupled to the processor; and

a data acquisition device coupled to the processor and the memo medium;

wherein the data acquisition device is operable to;

acquire a target data set; and

wherein the memory medium stores program instructions which are executable by the processor to;

determine a target discrete curve from the target data set, wherein the target discrete curve corresponds to a respective object in the target data set;

analyze one or more example target data sets to determine one or more example target discrete curves, wherein each of the one or more example target discrete curves corresponds to a data object or part of a data object in the one or more example target data sets;

characterize an object of interest to produce a mapped template discrete curve, wherein to characterize the object of interest the program instructions are executable to;

determine a template discrete curve from information regarding the object of interest, wherein the template discrete curve corresponds to the object of interest;

determine the mapping operator based on the determined template discrete curve and the one or more example target discrete curves;

map the template discrete curve to the mapped template discrete curve using the mapping operator;

perform curve matching on the target discrete curve and the mapped template discrete curve, wherein the mapped template discrete curve corresponds to an object of interest, wherein said performing curve matching computes a distance for the target discrete curve relative to the mapped template discrete curve, and wherein to perform curve matching on the target discrete curve and the mapped template discrete curve the program instructions are executable to determine whether the respective object in the target data set corresponds to the object of interest; and

generate curve matching results based on the distances.

70. A system for determining the presence of an object of interest in a target data set, the system comprising:

a computer system, comprising;

a processor; and

a memory medium coupled to the processor; and

a data acquisition device coupled to the processor and the memory medium;

wherein the data acquisition device is operable to;

acquire the target data set; and

wherein, the memory medium stores program instructions which are executable by the processor to;

determine a plurality of target discrete curves from the target data set, wherein each target discrete curve corresponds to a respective object in the target data set;

analyze one or more example target data sets to determine one or more example target discrete curves, wherein each of the one or more example target discrete curves corresponds to a data object or part of a data object in the one or more example target data sets;

characterize an object of interest to produce a mapped template discrete curve, wherein to characterize the object of interest the program instructions are executable to;

determine a template discrete curve from information regarding the object of interest, wherein the template discrete curve corresponds to the object of interest;

determine the mapping operator based on the determined template discrete curve and the one or more example target discrete curves; and

map the template discrete curve to the mapped template discrete curve using the mapping operator;

determine a plurality of target discrete curves from the target data set, wherein each of the target discrete curves corresponds to a respective object in the target data set;

for each of the target discrete curves, perform curve matching on each of the mapped target discrete curves and the mapped template discrete curve corresponding to the object of interest, wherein said performing curve matching computes a distance for the each of the target discrete curves relative to the mapped template discrete curve, and wherein to perform curve matching on each the target discrete curves and the mapped template discrete curve the program instructions are executable to determine whether the respective object in the target data set corresponds to the object of interest; and

generate curve matching results based on the distances.

71. The system of claim 70,

wherein, in determining the plurality of target discrete curves from the target data set, the program instructions we further executable by the processor to:

determine a plurality of initial target discrete curves from the target data set; and

map the plurality of initial target discrete curves to a respective plurality of mapped target discrete curves using the mapping operator, wherein the plurality of mapped target discrete curves comprises the plurality of target discrete curves; and

wherein, in performing curve matching on each of the target discrete curves and the mapped template discrete curve, the program instructions are further executable by the processor to;

perform curve matching on each of the mapped target discrete curves and the mapped template discrete curve.

72. A system for determining the presence of an object of interest in a target data set, the system comprising:

means for acquiring the target data set;

means for analyzing one or more example target data sets to determine one or more example target discrete curves, wherein each of the one or more example target discrete curves corresponds to a data object or part of a data object in the one or more example target data sets;

means for characterizing an object of interest to produce a mapped template discrete curve, wherein said means for characterizing the object of interest comprises;

means for determining a template discrete curve from information regarding the object of interest, wherein the template discrete curve corresponds to the object of interest;

means for determining the mapping operator based on the determined template discrete curve and the one or more example target discrete curves; and

means for mapping the template discrete curve to the mapped template discrete curve using the mapping operator;

means for determining a target discrete curve from the target data set, wherein the target discrete curve corresponds to a respective object in the target data set;

means for performing curve matching on the target discrete curve and the mapped template discrete curve, wherein the mapped template discrete curve corresponds to the object of interest, wherein said performing curve matching computes a distance for the target discrete curve relative to the mapped template discrete curve, and wherein said means for performing curve matching on the target discrete curve and the mapped template discrete curve comprises means for determining whether the respective object in the target data set corresponds to the object of interest; and

means for generating curve matching results based on the distances.

73. The system of claim 72,

wherein said determining the target discrete curve from the target data set comprises:

determining an initial target discrete curve from the target data set; and

mapping the initial target discrete curve to a mapped target discrete curve using the mapping operator, wherein the mapped target discrete curve comprises the target discrete curve; and

wherein said performing curve matching on the target discrete curve and the mapped template discrete curve comprises performing curve matching on the mapped target discrete curve and the mapped template discrete curve.

74. A system for determining the presence of an object of interest in a target data set, the system comprising:

means for acquiring the target data set;

means for determining a plurality of target discrete curves from the target data set, wherein each of the target discrete curves corresponds to a respective object in the target data set;

means for analyzing one or more example target data sets to determine one or more example target discrete curves, wherein each of the one or more example target discrete curves corresponds to a data object or part of a data object in the one or more example target data sets;

means for characterizing an object of interest to produce a mapped template discrete curve, wherein said characterizing the object of interest comprises;

means for determining a template discrete curve from information regarding the object of interest, wherein the template discrete curve corresponds to the object of interest;

means for determining the mapping operator based on the determined template discrete curve and the one or more example target discrete curves; and

means for mapping the template discrete curve to the mapped template discrete curve using the mapping operator;

means for performing curve matching on each of the target discrete curves and the mapped template discrete curve corresponding to the object of interest, wherein said performing curve matching computes a distance for the each of the target discrete curves relative to the mapped template discrete curve, and wherein said performing curve matching on the target discrete curves and the mapped template discrete curve comprises determining whether the respective objects in the target data set correspond to the object of interest; and

means for generating curve matching results based on the distances.

75. The system of claim 74,

wherein said determining the plurality of target discrete curves from the target data set comprises:

determining a plurality of initial target discrete curves from the target data set; and

mapping the plurality of initial target discrete curves to a respective plurality of mapped target discrete curves using the mapping operator, wherein the plurality of mapped target discrete curves comprises the plurality of target discrete curves; and

wherein said performing curve matching on each of the target discrete curves and the mapped template discrete curve comprises performing curve matching on each of the mapped target discrete curves and the mapped template discrete curve.

76. A method for characterizing an object of interest for a pattern matching application, the method comprising:

receiving data containing the object of interest;

determining a template discrete curve from the data, wherein the template discrete curve corresponds to the object of interest in the data; and

analyzing the object of interest and one or more example target data sets to determine one or more terms for a mapping operator, wherein the mapping operator comprises a weight vector;

mapping the template discrete curve to a mapped template discrete curve using the mapping operator, wherein said tapping comprises;

applying the weight vector terms respectively to corresponding points in the template discrete curve;

wherein the mapped template discrete curve is useable to perform pattern matching to locate instances of the object of interest in acquired target data.

77. The method of claim 76,

wherein the mapping operator is a weighting operator.

78. The method of claim 76,

wherein the mapping operator operates to emphasize differences between respective data objects.

79. The method of claim 76, further comprising:

analyzing the object of interest and one or more example target data sets to determine at least one parameter for the mapping operator; and

configuring the mapping operator according to the determined at least one parameter;

wherein said mapping uses the configured mapping operator.

80. The method of claim 79,

wherein the at least one parameter is used to create a distance between mapped discrete curves corresponding to the object of interest and mapped discrete curves corresponding to objects that are not of interest.

81. The method of claim 76, further comprising:

receiving first information regarding the object of interest;

receiving second information regarding one or more objects that are not of interest;

determining at least one parameter for the mapping operator based on the first information and the second information; and

configuring the mapping operator according to the determined at least one parameter.

82. The method of claim 81,

wherein the at least one parameter is used to enhance a distance between mapped discrete curves corresponding to the object of interest and mapped discrete curves corresponding to objects that are not of interest.

83. The method of claim 76,

wherein said determining the template discrete curve from the data comprises performing edge detection on the data to determine one or more edges of the object of interest present in the data.

84. The method of claim 83, further comprising:

determining a plurality of template discrete curves from the data by performing edge detection on the data to determine a plurality of edges of the object of interest present in the data, wherein the plurality of template discrete curves are based on the plurality of edges of the object of interest.

85. A computer readable memory medium which stores program instructions for characterizing an object of interest for a pattern matching application, wherein the program instructions are executable to perform:

receiving data containing the object of interest;

determining a template discrete curve from the data, wherein the template discrete curve corresponds to the object of interest in the data;

analyzing the object of interest and one or more example target data sets to determine one or more terms for the mapping operator wherein the mapping operator comprises a weight vector; and

mapping the template discrete curve to a mapped template discrete curve using the mapping operator, wherein said mapping comprises;

applying the weight vector terms respectively to corresponding points in the template discrete curve;

wherein the mapped template discrete curve is useable to perform pattern matching to locate instances of the object of interest in acquired target data.

86. The computer readable memory medium of claim 85,

wherein the mapping operator is a weighting operator.

87. The computer readable memory medium of claim 85,

wherein the mapping operator operates to emphasize differences between respective data objects.

88. The computer readable memory medium of claim 85, wherein the program instructions are further executable to perform:

analyzing the object of interest and one or more example target data sets to determine at least one parameter for the mapping operator; and

configuring the mapping operator according to the determined at least one parameter;

wherein said mapping uses the configured mapping operator.

89. The computer readable memory medium of claim 85,

wherein the one or more terms are used to create a distance between mapped discrete curves corresponding to the object of interest and mapped discrete curves corresponding to objects that are not of interest.

90. The computer readable memory medium of claim 85, wherein the program instructions are further executable to perform:

receiving first information regarding the object of interest;

receiving second information regarding one or more objects that are not of interest;

determining at least one parameter for the mapping operator based on the first information and the second information; and

configuring the mapping operator according to the determined at least one parameter.

91. The computer readable in memory medium of claim 90, wherein the at least one parameter is used to enhance a distance between mapped discrete curves corresponding to the object of interest and mapped discrete curves corresponding to objects tat are not of interest.

92. The computer readable memory medium of claim 85,

wherein said determining the template discrete curve from the data comprises performing edge detection on the data to determine one or more edges of the object of interest present in the data.

93. The computer readable memory medium of claim 92, wherein the program instructions are further executable to perform:

determining a plurality of template discrete curves from the data by performing edge detection on the data to determine a plurality of edges of the object of interest present in the data, wherein the plurality of template discrete curves are based on the plurality of edges of the object of interest.

94. A system for characterizing an object of interest for a pattern matching application, the system comprising:

a computer system, comprising;

a processor; and

a memory medium coupled to the processor; and

wherein the memory medium stores program instructions which are executable by the processor to;

receive data containing the object of interest;

determine a template discrete curve from the data, wherein the template discrete curve corresponds to the object of interest in the data;

analyze the object of interest and one or more example target data sets to determine one or more terms for the mapping operator, wherein the mapping operator comprises a weight vector; and

map the template discrete curve to a mapped template discrete curve using the mapping operator, wherein to map the template discrete curve the program instructions are executable to;

apply the weight vector terms respectively to corresponding points in the template discrete curve;

wherein the mapped template discrete curve is useable to perform pattern matching to locate instances of the object of interest in acquired target data.

95. A method for performing curve matching between a target discrete curve and a template discrete curve, the method comprising:

mapping a template discrete curve to a mapped template discrete curve using a mapping operator, including characterizing an object of interest to produce the mapped template discrete curve, wherein said characterizing the object of interest comprises;

determining the template discrete curve from information regarding the object of interest, wherein the template discrete curve corresponds to the object of interest;

analyzing the mapped template discrete curve and one or more example target discrete curves generated from one or more example target data sets to determine at least one parameter for the mapping operator;

configuring the mapping operator according to the determined at least one parameter;

performing curve matching on a target discrete curve and the mapped template discrete curve, wherein said performing curve matching computes a distance for the target discrete curve relative to the mapped template discrete curve; and

generating curve matching results based on the distances.

96. The method of claim 95,

wherein the at least one parameter is used to increase a distance between mapped discrete curves corresponding to the object of interest and mapped discrete curves corresponding to objects that are not of interest.

97. A method for performing curve matching between a target discrete curve and a template discrete curve, the method comprising:

receiving first information regarding an object of interest;

receiving second information regarding one or more objects that are not of interest;

determining at least one parameter for the mapping operator based on the first information and the second information, wherein the at least one parameter is determined to enhance a distance between mapped discrete curves corresponding to an object of interest and mapped discrete curves corresponding to the one or more objects that are not of interest; and

configuring the mapping operator according to the determined at least one parameter;

mapping a template discrete curve to a mapped template discrete curve using the mapping operator;

performing curve matching on a target discrete curve and the mapped template discrete curve, wherein said performing curve matching computes a distance for the target discrete curve relative to the mapped template discrete curve; and

generating curve matching results based on the distances.

98. A method for performing curve matching between a target discrete curve and a template discrete curve, the method comprising:

mapping a template discrete curve to a mapped template discrete curve using a mapping operator;

performing curve matching on a target discrete curve and the mapped template discrete curve, wherein said performing curve matching computes a distance for the target discrete curve relative to the mapped template discrete curve; and

generating curve matching results based on the distances;

wherein the mapping operator comprises a weight vector w;

wherein the template discrete curve comprises a first vector;

wherein said weight vector w, and said first vector have the same number of elements; and

wherein said mapping the template discrete curve to the mapped template discrete curve comprises;

multiplying each element of the weight vector w with corresponding elements in the first vector to generate a second vector, wherein elements of the second vector comprise the mapped template discrete curve.

99. A computer readable memory medium which stores program instructions for performing curve matching between a target discrete curve and a template discrete curve, wherein the program instructions are executable to perform:

acquiring a target data set;

determining a target discrete curve from the target data set, wherein the target discrete curve corresponds to a respective object in the target data set;

analyzing the mapped template discrete curve and one or more example target discrete curves generated from one or more example target data sets to determine at least one parameter for the mapping operator;

configuring the mapping operator according to the determined at least one parameter;

mapping a template discrete curve to a mapped template discrete curve using a mapping operator, including characterizing an object of interest to produce the mapped template discrete curve, wherein the mapped template discrete curve corresponds to the object of interest, and wherein said characterizing the object of interest comprises;

determining a template discrete curve corresponding to the object of interest from information regarding the object of interest;

performing curve matching on the target discrete curve and the mapped template discrete curve, wherein said performing curve matching computes a distance for the target discrete curve relative to the mapped template discrete curve, wherein said performing curve matching on the mapped target discrete curve and the mapped template discrete curve comprises determining whether the respective object in the target data set corresponds to the object of interest; and

generating curve matching results based on the distances.

100. The computer readable memory medium of claim 99,

wherein the at least one parameter is used to increase a distance between mapped sequences corresponding to the object of interest and mapped discrete curves corresponding to objects that are not of interest.

101. A computer readable memory medium which stores program instructions for performing curve matching between a target discrete curve and a template discrete curve, wherein the program instructions are executable to perform:

receiving first information regarding an object of interest;

receiving second information regarding one or more objects that are not of interest;

determining at least one parameter for a mapping operator based on the first information and the second information, wherein the at least one parameter is determined to enhance a distance between mapped discrete curves corresponding to an object of interest and mapped discrete curves corresponding to the one or more objects that are not of interest;

configuring the mapping operator according to the determined at least one parameter;

mapping a template discrete curve to a mapped template discrete curve using a mapping operator;

performing curve matching on a target discrete curve and the mapped template discrete curve, wherein said performing curve matching computes a distance for the target discrete curve relative to the mapped template discrete curve; and

generating curve matching results based on the distances.

102. A computer-readable memory medium which stores program instructions for performing curve matching between a target discrete curve and a template discrete curve, wherein the program instructions are executable to perform:

mapping a template discrete curve to a mapped template discrete curve using a mapping operator;

performing curve matching on a target discrete curve and the mapped template discrete curve, wherein said performing curve matching computes a distance for the target discrete curve relative to the mapped template discrete curve; and

generating curve matching results based on the distances;

wherein the mapping operator comprises a weight vector W;

wherein the template discrete curve comprises a first vector;

wherein said weight vector W, and said first vector have the same number of elements; and

wherein said mapping the template discrete curve to the mapped template discrete curve comprises;

multiplying each element of the weight vector W with corresponding elements in the first vector to generate a second vector, wherein elements of the second vector comprise the mapped template discrete curve.

103. A method for characterizing an object of interest for a pattern matching application, the method comprising:

receiving data containing the object of interest;

determining a template discrete curve from the data, wherein the template discrete curve corresponds to the object of interest in the data; and

analyzing the object of interest and one or more example target data sets to determine at least one parameter for a mapping operator;

configuring the mapping operator according to the determined at least one parameter;

mapping the template discrete curve to a mapped template discrete curve using the mapping operator;

wherein the mapped template discrete curve is useable to perform pattern matching to locate instances of the object of interest in acquired target data.

104. The method of claim 103,

wherein the at least one parameter is used to create a distance between mapped discrete curves corresponding to the object of interest and mapped discrete curves corresponding to objects that are not of interest.

105. A method for characterizing an object of interest for a pattern matching application, the method comprising:

receiving first information regarding the object of interest, including receiving data containing the object of interest;

determining a template discrete curve from the data, wherein the template discrete curve corresponds to the object of interest in the data;

receiving second information regarding one or more objects that are not of interest;

determining at least one parameter for the mapping operator based on the first information and the second information;

configuring the mapping operator according to the determined at least one parameter;

mapping the template discrete curve to a mapped template discrete curve using a mapping operator;

wherein the mapped template discrete curve is useable to perform pattern matching to locate instances of the object of interest in acquired target data.

106. The method of claim 105,

wherein the at least one parameter is used to enhance a distance between mapped discrete curves corresponding to the object of interest and mapped discrete curves corresponding to objects that are not of interest.

107. A computer readable memory medium which stores program instructions for characterizing an object of interest for a pattern matching application, wherein the program instructions are executable to perform:

receiving data containing the object of interest;

determining a template discrete curve from the data, wherein the template discrete curve corresponds to the object of interest in the data;

analyzing the object of interest and one or more example target data sets to determine at least one parameter for the mapping operator; and

configuring the mapping operator according to the determined at least one parameter; and

mapping the template discrete curve to a mapped template discrete curve using the mapping operator;

wherein the mapped template discrete curve is useable to perform pattern matching to locate instances of the object of interest in acquired target data.

108. The computer readable memory medium of claim 107,

wherein the at least one parameter is used to create a distance between mapped discrete curves corresponding to the object of interest and mapped discrete curves corresponding to objects that are not of interest.

109. A computer readable memory medium which stores program instructions for characterizing an object of interest for a pattern matching application, wherein the program instructions are executable to perform:

receiving first information regarding the object of interest including receiving data containing the object of interest;

determining a template discrete curve from the data, wherein the template discrete curve corresponds to the object of interest in the data;

receiving second information, regarding one or more objects that are not of interest;

determining at least one parameter for the mapping operator based on the first information and the second information; and

configuring the mapping operator according to the determined at least one parameter; and

mapping the template discrete curve to a mapped template discrete curve using the mapping operator;

wherein the mapped template discrete curve is useable to perform pattern matching to locate instances of the object of interest in acquired target data.

110. The computer readable memory medium of claim 109,

wherein the at least one parameter is used to enhance a distance between mapped discrete curves corresponding to the object of interest and mapped discrete curves corresponding to objects that are not of interest.