Fingerprint biometric machine representations based on triangles

• US 20060104484A1
• Filed: 11/16/2004
• Published: 05/18/2006
• Est. Priority Date: 11/16/2004
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Pankanti, Sharathchandra, Ratha, Nalini Kanta, Bolle, Rudolf Maarten, Connell, Jonathan Hudson
• Application Number:
  US10/989,595
• Publication Number:
  US 20060104484A1
• Time in Patent Office: Days
• US Class Current: 382/115
• CPC Class Codes: G06V 40/10 Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
• CPC Class Codes: G06V 40/1353 Extracting features related to minutiae or pores

Abstract

There is provided an apparatus, method, and program storage device for representing biometrics. The apparatus includes a biometric feature extractor and a transformer. The biometric feature extractor is for extracting features corresponding to a biometric depicted in an image, and for defining one or more sets of one or more geometric shapes by one or more of the features. Each of the one or more geometric shapes has one or more geometric features that is invariant with respect to a first set of transforms applied to at least a portion of the image. The transformer is for applying the first set of transforms to the at least a portion of the image to obtain one or more feature representations that include one or more of the one or more geometric features, and for applying a second set of transforms to the one or more feature representations to obtain one or more transformed feature representations.

Claims

1. An apparatus for representing biometrics, comprising:

a biometric feature extractor for extracting features corresponding to a biometric depicted in an image, for defining at least one set of at least one geometric shape by at least some of the features, each of the at least one geometric shape having at least one geometric feature that is invariant with respect to a first set of transforms applied to at least a portion of the image; and

a transformer for applying the first set of transforms to the at least a portion of the image to obtain at least one feature representation that includes at least one of the at least one geometric feature, and for applying a second set of transforms to the at least one feature representation to obtain at least one transformed feature representation.

2. The apparatus of claim 1, wherein the at least one transformed feature representation has at least one element that is not correlated with other elements in the at least one transformed feature representation, wherein the at least one element and at least one of the other elements form an element set of elements that are mutually uncorrelated, the element set for representing the biometric.

3. The apparatus of claim 2, wherein the at least one transformed feature representation has the at least one element that is not correlated with the other elements in the at least one transformed feature representation by more than a correlation tolerance.

4. The apparatus of claim 2, wherein at least one of the other elements that is correlated is omitted from the element set.

5. The apparatus of claim 2, wherein the element set is used as an index to represent at least one of the biometric and the image for at least one of hashing, an identification process, and a selection process.

6. The apparatus of claim 5, wherein the index is an n-based index, a magnitude of a number of bits of the n-based index is determined by a degree of correlation between at least two transformed feature representation axes,

7. The apparatus of claim 2, wherein the at least one transformed feature representation has at least one uncorrelated element and at least one correlated element arranged in descending order by a degree of correlation, at least one of the at least one correlated element omitted so that remaining ones of the at least one uncorrelated element and the at least one correlated element form an element set of at least two elements that are mutually uncorrelated, the element set being quantized into an n-bit index used to represent the biometric.

8. The apparatus of claim 7, where the quantization of the element set at least one of deletes geometric shapes that exceed a correlation threshold, permits only a maximum number of any of the least one geometric shape, reduces any of the at least one geometric shape to a simpler representation, and reduces any of the at least one geometric shape to a single unique identifier.

9. The apparatus of claim 1, further comprising a photometric feature extractor for extracting from the image at least one photometric feature that is non-geometric and invariant with respect to any rigid transform applied to the portion of the image, each of the at least one photometric feature being associated with a region of the image related to a respective one of the at least one geometric feature, and wherein the at least one feature representation further includes at least one of the at least one photometric feature.

10. The apparatus of claim 9, wherein the region is defined by at least one of the at least one geometric shape, an interior of the at least one geometric shape, an area within a tolerance distance of the at least one geometric shape, a curvilinear shape that has a boundary on which lays at least three vertices of the at least one geometric shape, a circular region that has a boundary on which lay at least three vertices of the at least one geometric shape.

11. The apparatus of claim 1, further comprising an ordering device for arranging the at least one element and the other elements of the at least one transformed feature representation in descending order by a degree of correlation.

12. The apparatus of claim 11, wherein at least one of the at least one geometric feature and at least one of the features extracted from the image are combined before said ordering device executes an ordering process.

13. The apparatus of claim 11, wherein said ordering device executes an ordering process for at least one of the at least one geometric feature and thereafter for at least one of the features extracted from the image, and then combines corresponding ordering results.

14. The apparatus of claim 1, wherein the first set of transforms is invariant with respect to a similarity transformation.

15. The apparatus of claim 1, wherein an enrollment image is represented by an enrollment template, the enrollment template being at least one of the at least one geometric shape ordered by a degree of non-correlation of any of the at least one geometric feature associated with the at least one of the at least one geometric shape.

16. The apparatus of claim 1, further comprising:

at least one database for storing enrollment templates therein;

a query input that receives a query template, the query template being at least one of the at least one geometric shape ordered by a degree of non-correlation of any of the at least one geometric feature associated with the at least one of the at least one geometric shape; and

a comparator for comparing the query template to the stored enrollment templates, and outputting a comparison result for identifying at least one enrolled image most similar to a query image corresponding to the query template.

17. The apparatus of claim 16, wherein a similarity between an enrolled image and the query image is ascertained by a number of indices common in the query template and an enrollment template respectively corresponding thereto.

18. The apparatus of claim 16, wherein a similarity between an enrolled image and a query image is ascertained by pairs of selected enrolled and query geometric shapes that index to common indices in the query template and an enrollment template respectively corresponding thereto and that are related to each other by a common similarity transform.

19. A method for representing biometrics, comprising the steps of:

extracting features corresponding to a biometric depicted in an image;

defining at least one set of at least one geometric shape by at least some of the features, each of the at least one geometric shape having at least one geometric feature that is invariant with respect to a first set of transforms applied to at least a portion of the image;

applying the first set of transforms to the at least a portion of the image to obtain at least one feature representation that includes at least one of the at least one geometric feature; and

applying a second set of transforms to the at least one feature representation to obtain at least one transformed feature representation.

20. The method of claim 19, wherein the at least one transformed feature representation has at least one element that is not correlated with other elements in the at least one transformed feature representation, and wherein the at least one element and at least one of the other elements form an element set of elements that are mutually uncorrelated, the element set for representing the biometric.

21. The method of claim 20, wherein the element set is used as an index to represent at least one of the biometric and the image for at least one of hashing, an identification process, and a selection process.

22. The method of claim 20, further comprising the steps of:

arranging, in descending order by a degree of correlation, at least one uncorrelated element and at least one correlated element of the at least one transformed feature representation;

omitting at least one of the at least one correlated element so that remaining ones of the at least one uncorrelated element and the at least one correlated element form an element set of at least two elements that are mutually uncorrelated; and

quantizing the element set into an n-bit index used to represent the biometric.

23. The method of claim 19, further comprising the step of extracting from the image at least one photometric feature that is non-geometric and invariant with respect to any rigid transform applied to the portion of the image, each of the at least one photometric feature being associated with a region of the image related to a respective one of the at least one geometric feature, and wherein the at least one feature representation further includes at least one of the at least one photometric feature.

24. The method of claim 19, further comprising the step of arranging the at least one element and the other elements of the at least one transformed feature representation in descending order by a degree of correlation.

25. The method of claim 19, further comprising the steps of:

storing enrollment templates;

receiving a query template, the query template being at least one of the at least one geometric shape ordered by a degree of non-correlation of any of the at least one geometric feature associated with the at least one of the at least one geometric shape;

comparing the query template to the stored enrollment templates; and

outputting a comparison result for identifying at least one enrolled image most similar to a query image corresponding to the query template.

26. A program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform method steps for representing biometrics as recited in claim 19.