MATCHING METHODS AND APPARATUS USING LANDMARK POINTS IN A PRINT

• US 20070263913A1
• Filed: 05/15/2006
• Published: 11/15/2007
• Est. Priority Date: 05/15/2006
• Status: Abandoned Application

• Current Assignee: Motorola, Inc. (Motorola Solutions, Inc.)
• Original Assignee: Motorola, Inc. (Motorola Solutions, Inc.)
• Inventors: BAVARIAN, BEHNAM, DANIEL, SAM, WABGAONKAR, HARSHAWARDHAN, LO, PETER
• Application Number:
  US11/383,449
• Publication Number:
  US 20070263913A1
• Time in Patent Office: Days
• US Class Current: 382/125
• CPC Class Codes: G06V 40/1371 Matching features related to minutiae or pores

Abstract

A method for comparing a search print to a plurality of file prints includes performing a gray scale-based matching process, wherein cross-section profile pairs are determined between minutiae and landmark points in a search print and corresponding respondent prints, and individual similarity measures are computed based on the cross-section profile pairs using an elastic correlation process. A composite similarity measure is computed from the individual similarity measures. Optimizations such as segment outlier optimization (to eliminate outlier segments/minutiae points from the composite similarity measure computation) and adjusting the landmark point location in the search or respondent print can be implemented to maximize the composite similarity measure for a given respondent print. This maximized composite similarity measure can be combined with a similarity measure from another print matcher such as another gray scale-based matcher.

Claims

1. A method for comparing a search print to a plurality of file prints, the method comprising the steps of:

obtaining a search print landmark point and a plurality of predetermined search print minutiae points located in a first geographic region of a search print;

obtaining, for each file print in a set of selected file prints, a file print landmark point and a plurality of file print minutiae points that are mated to at least a portion of the plurality of predetermined search print minutiae points, the file print landmark point and the file print mated minutiae points being located in a second geographic region of the selected file print; and

for each file print in the set of selected file prints,

determining, for at least a portion of the file print minutiae points, a matched profile pair comprising a first cross-section profile between the file print minutia point and the file print landmark point and a second cross-section profile between the corresponding search print mated minutiae and the search print landmark point, and an individual similarity measure that is indicative of the similarity between the first and second cross-section profiles; and

computing a composite similarity measure based on the individual similarity measures, the composite similarity measure being indicative of similarity between the first geographic region in the search print and the second geographic region in the file print.

2. The method of claim 1 further comprising the steps of;

for each matched profile pair corresponding to a file print in the set of selected file prints,

comparing the individual similarity measures to a threshold; and

determining a maximum composite similarity measure by eliminating from the composite similarity measure computation at least a portion of the individual similarity measures that fall below the threshold.

3. The method of claim 2, wherein each composite similarity measure is combined with at least one other similarity measure for the corresponding file print to generate a combined similarity measure, wherein the at least one other similarity measure is computed based on a gray scale image of the search print and corresponding gray-scale images of the file prints in the set of selected file prints.

4. The method of claim 3, wherein the at least one other similarity measure that is computed based on a gray scale image of the search print and corresponding gray-scale images of the file prints in the set of selected file prints is computed using a method comprising the steps of, for each selected file print:

for each possible combination of mated minutiae pairs in the first and second subsets,

selecting a first pair of minutiae points from the plurality of predetermined search print minutiae points and a second pair of corresponding mated minutiae points from the file print minutiae points,

generating a first segment based on the first pair of minutiae points and a second segment based on the second pair of minutiae points,

generating a third cross-section profile based on the first segment and a fourth cross-section profile based on the second segment,

computing a second individual similarity measure that is indicative of the similarity between the third cross-section profile and the fourth cross-section profile, and

comparing the second individual similarity measure to a second threshold; and

computing a second composite similarity measure based on the second individual similarity measures associated with the third and fourth cross-section profiles, wherein a second maximum similarity measure, which is the at least one other similarity measure, is computed by eliminating from the second composite similarity measure computation at least a portion of the second individual similarity measures that fall below the second threshold.

5. The method of claim 1, wherein the search print and the file prints in the set of selected file prints are stored as gray scale images, and determining each of the cross-section profiles comprises the steps of:

determining a pixel location pair corresponding to the landmark point and the minutiae point;

sampling the gray scale image at a plurality of pixel locations between the pixel location pair to generate a plurality of sampled pixel locations;

obtaining a plurality of gray scale values corresponding to the plurality of sampled pixel locations; and

generating the cross-section profile based on the plurality of gray scale values.

6. The method of claim 1 further comprising the steps of:

for each file print in the set of selected file prints,

adjusting one of the search print landmark point and the file print landmark point location;

determining corresponding individual similarity measures based on the adjusted landmark point location; and

computing the corresponding composite similarity measure based on the adjusted landmark point location.

7. The method of claim 6 further comprising the step of computing a maximum composite similarity measure by iteratively adjusting the landmark point location, computing the corresponding composite similarity measure and maintaining the maximum composite similarity measure until a stopping criterion is reached.

8. The method of claim 7, wherein the stopping criterion is associated with a predetermined search region around the landmark point that is being adjusted.

9. The method of claim 1, wherein the landmark points are each one of a core, a delta and a designated landmark point.

10. The method of claim 1 further comprising the steps of:

receiving an initial set of file prints, each file print in the initial set comprising a file print landmark point and a plurality of file print minutiae points mated to at least a portion of the plurality of predetermined search print minutiae points; and

for each file print in the initial set of file prints,

comparing the first geographic region of the search print to the second geographic region of the file print using the file and search print landmarks points and the plurality of file print minutiae points and corresponding mated search print minutiae points to generate an initial geographic region similarity measure;

comparing the initial geographic region similarity measure to a threshold; and

generating the set of selected file prints by excluding from the initial set of file prints those file prints associated with an initial geographic similarity measure that is less than the threshold.

11. The method of claim 1, wherein the search print and the set of selected file prints comprise one of fingerprints, palm prints and toe prints.

12. The method of claim 1 further comprising the steps of:

for each file print in the set of selected file prints,

comparing each of the plurality of file print minutia points to a selection criterion; and

excluding from the composite similarity measure computation those file print minutiae points that do not meet the selection criterion.

13. Apparatus for comparing a search print to a plurality of file prints, the apparatus comprising:

a memory element storing a search print landmark point and a plurality of predetermined search print minutiae points located in a first geographic region of a search print, and further storing, for each file print in a set of selected file prints, a file print landmark point and a plurality of file print minutiae points that are mated to at least a portion of the plurality of predetermined search print minutiae points, the file print landmark point and the file print mated minutiae points being located in a second geographic region of the selected file print; and

a processing device configured for performing the following steps for each file print in the set of selected file prints,

determining, for at least a portion of the file print minutiae points, a matched profile pair comprising a first cross-section profile between the file print minutia point and the file print landmark point and a second cross-section profile between the corresponding search print mated minutiae and the search print landmark point, and an individual similarity measure that is indicative of the similarity between the first and second cross-section profiles; and

computing a composite similarity measure based on the individual similarity measures, the composite similarity measure being indicative of similarity between the first geographic region in the search print and the second geographic region in the file print.

14. The apparatus of claim 13, wherein the memory element further storing the search print and the file prints in the set of selected file prints as gray scale images, and the processing device determining each of the cross-section profiles comprises the processing device performing the steps of:

determining a pixel location pair corresponding to the landmark point and the minutiae point;

sampling the gray scale image at a plurality of pixel locations between the pixel location pair to generate a plurality of sampled pixel locations;

obtaining a plurality of gray scale values corresponding to the plurality of sampled pixel locations; and

generating the cross-section profile based on the plurality of gray scale values.

15. The apparatus of claim 13, wherein the memory element further storing pre-computed and compressed cross-section profiles, and the processing device determining the cross-section profiles comprises retrieving at least a portion of the cross-section profiles from the memory element.

16. The apparatus of claim 15, wherein the cross-section profiles are coded with a pre-determined number of bits of quantization and processed using run-length encoding to generate the compressed cross-section profiles.

17. The apparatus of claim 13, wherein the apparatus comprises at least one of a microprocessor executing code, an Application Specific Integrated Circuit (ASIC), a field programmable gate array (FPGA) and a state machine.

18. A computer-readable storage element having computer readable code stored thereon for programming a computer to perform a method for comparing a search print to a plurality of file prints, the method comprising the steps of:

obtaining a search print landmark point and a plurality of predetermined search print minutiae points located in a first geographic region of a search print;

obtaining, for each file print in a set of selected file prints, a file print landmark point and a plurality of file print minutiae points that are mated to at least a portion of the plurality of predetermined search print minutiae points, the file print landmark point and the file print mated minutiae points being located in a second geographic region of the selected file print; and

for each file print in the set of selected file prints,

determining, for at least a portion of the file print minutiae points, a matched profile pair comprising a first cross-section profile between the file print minutia point and the file print landmark point and a second cross-section profile between the corresponding search print mated minutiae and the search print landmark point, and an individual similarity measure that is indicative of the similarity between the first and second cross-section profiles; and

computing a composite similarity measure based on the individual similarity measures, the composite similarity measure being indicative of similarity between the first geographic region in the search print and the second geographic region in the file print.

19. The computer-readable storage medium of claim 18, wherein the computer readable storage medium comprises at least one of a hard disk, a CD-ROM, an optical storage device and a magnetic storage device.

20. The computer readable storage medium of claim 18, wherein the search print and the file prints in the set of selected file prints are stored as gray scale images, and programming the computer for determining each of the cross-section profiles comprises programming the computer to perform the steps of:

determining a pixel location pair corresponding to the landmark point and the minutiae point;

sampling the gray scale image at a plurality of pixel locations between the pixel location pair to generate a plurality of sampled pixel locations;

obtaining a plurality of gray scale values corresponding to the plurality of sampled pixel locations; and

generating the cross-section profile based on the plurality of gray scale values.