Dynamic handwriting verification and handwriting-based user authentication

• US 9,235,748 B2
• Filed: 11/14/2013
• Issued: 01/12/2016
• Est. Priority Date: 11/14/2013
• Status: Active Grant

• Current Assignee: Wacom Co Limited (Wacom)
• Original Assignee: Wacom Co Limited (Wacom)
• Inventors: Mettyear, Nicholas
• Primary Examiner(s): Akhavannik, Hadi
• Application Number:
  US14/080,723
• Publication Number:
  US 20150131874A1
• Time in Patent Office: 789 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06V 10/754 involving a deformation of the sample pattern or of the reference pattern; Elastic matching
• CPC Class Codes: G06V 30/1423 the instrument generating sequences of position coordinates corresponding to handwriting preprocessing or recognising digital ink G06V30/32
• CPC Class Codes: G06V 30/2268 using stroke segmentation
• CPC Class Codes: G06V 40/30 Writer recognition; Reading and verifying signatures
• CPC Class Codes: G06V 40/33 based only on signature image, e.g. static signature recognition
• CPC Class Codes: G06V 40/394 Matching; Classification

Abstract

Handwriting verification methods and related computer systems, and handwriting-based user authentication methods and related computer systems are disclosed. A handwriting verification method comprises obtaining a handwriting test sample containing a plurality of available parameters, extracting geometric parameters, deriving geometric features comprising an x-position value and a y-position value for each of a plurality of feature points in the test sample, performing feature matching between geometric features of the test sample and a reference sample, determining a handwriting verification result based at least in part on the feature matching, and outputting the handwriting verification result. The geometric features may further comprise values derived from the geometric parameters, such as direction and curvature values. The handwriting verification result can be further based on a count of unlinked feature points. Handwriting-based user authentication methods can employ such handwriting verification methods, or other handwriting verification methods.

Claims

1. A handwriting verification method executed in a computer system, the method comprising:

obtaining a handwriting test sample containing a plurality of available parameters, wherein the plurality of available parameters comprises geometric parameters and one or more non-geometric parameters;

extracting the geometric parameters from the plurality of available parameters;

based on the geometric parameters, deriving geometric features comprising an x-position value and a y-position value for each of a plurality of evenly distributed feature points in the handwriting test sample;

performing feature mapping by finding mappings between one or more of the evenly distributed feature points in the test sample and one or more evenly distributed feature points in the reference sample, wherein the feature mapping includes;

(i) selecting a feature point in the reference sample, and

(ii) based on a pseudo-random value, determining whether to (a) remove a link from a selected point in the reference sample, or (b) define a new link between the selected feature point in the reference sample and a selected feature point in the test sample; and

determining a handwriting verification result based at least in part on the mappings.

2. The method of claim 1, wherein the finding mappings is performed in a simulated-annealing process.

3. The method of claim 1, wherein the determining whether to remove a link or define a new link is biased towards defining a new link over removing an existing link based on the value of the constant.

4. A non-transitory computer-readable medium having stored thereon computer-executable instructions configured to, when executed, cause a computer system to:

obtain a handwriting test sample containing a plurality of available parameters, wherein the plurality of available parameters comprises geometric parameters and one or more non-geometric parameters;

extract the geometric parameters from the plurality of available parameters;

based on the geometric parameters, derive geometric features comprising an x-position value and a y-position value for each of a plurality of evenly distributed feature points in the handwriting test sample;

perform feature mapping by finding mappings between one or more of the evenly distributed feature points in the test sample and one or more evenly distributed feature points in the reference sample, wherein the feature mapping includes;

(i) selecting a feature point in the reference sample, and

(ii) based on a pseudo-random value, determining whether to (a) remove a link from a selected point in the reference sample, or (b) define a new link between the selected feature point in the reference sample and a selected feature point in the test sample; and

determine a handwriting verification result based at least in part on the mappings.

5. The computer-readable medium of claim 4, wherein said finding mappings is performed in a simulated-annealing process.

6. The computer-readable medium of claim 4, wherein said determining whether to remove a link or define a new link is biased towards defining a new link over removing an existing link based on the value of the constant.

7. A system comprising one or more computing devices programmed to:

obtain a handwriting test sample containing a plurality of available parameters, wherein the plurality of available parameters comprises geometric parameters and one or more non-geometric parameters;

extract the geometric parameters from the plurality of available parameters;

based on the geometric parameters, derive geometric features comprising an x-position value and a y-position value for each of a plurality of evenly distributed feature points in the handwriting test sample;

perform feature mapping by finding mappings between one or more of the evenly distributed feature points in the test sample and one or more evenly distributed feature points in the reference sample, wherein the feature mapping includes;

(i) selecting a feature point in the reference sample, and

(ii) based on a pseudo-random value, determining whether to (a) remove a link from a selected point in the reference sample, or (b) define a new link between the selected feature point in the reference sample and a selected feature point in the test sample; and

determine a handwriting verification result based at least in part on the mappings.

8. The system of claim 7, wherein said finding mappings is performed in a simulated-annealing process.

9. The system of claim 7, wherein said determining whether to remove a link or define a new link is biased towards defining a new link over removing an existing link based on the value of the constant.