System and method for three-dimensional biometric data feature detection and recognition

• US 8,391,590 B2
• Filed: 03/04/2010
• Issued: 03/05/2013
• Est. Priority Date: 03/04/2010
• Status: Active Grant

• Current Assignee: Flashscan3D, LLC
• Original Assignee: Flashscan3D, LLC
• Inventors: Yalla, Veeraganesh, Boles, Colby, Daley, Raymond Charles, Fleming, Robert Kyle
• Primary Examiner(s): Rahmjoo, Mike
• Application Number:
  US12/717,347
• Publication Number:
  US 20110216948A1
• Time in Patent Office: 1,097 Days
• Field of Search: 382/154, 382/118, 382/115, 382/116, 382/132, 382/119, 382/120, 382/124, 382/125, 382/126, 340/5.53, 340/5.83
• US Class Current: 382/154
• CPC Class Codes: G06F 18/00 Pattern recognition
• CPC Class Codes: G06V 20/64 Three-dimensional objects
• CPC Class Codes: G06V 20/653 by matching three-dimensional models, e.g. conformal mapping of Riemann surfaces
• CPC Class Codes: G06V 40/12 Fingerprints or palmprints
• CPC Class Codes: G06V 40/1312 direct reading, e.g. contactless acquisition

Abstract

The system includes a 3D feature detection module and 3D recognition module 202. The 3D feature detection module processes 3D surface map of a biometric object, wherein the 3D surface map includes a plurality of 3D coordinates. The 3D feature detection module determines whether one or more types of 3D features are present in the 3D surface map and generates 3D feature data including 3D coordinates and feature type for the detected features. The 3D recognition module compares the 3D feature data with biometric data sets for identified persons. The 3D recognition module determines a match between the 3D feature data and one of the biometric data sets when a confidence value exceeds a threshold.

Claims

1. A method for three-dimensional (3D) feature detection, comprising:

receiving a 3D surface map of a fingerprint, wherein the 3D surface map includes a plurality of points having 3D coordinates;

generating one or more subsets of the plurality of points of the 3D surface map;

processing the 3D surface map to detect at least one 3D feature within one or more of the subsets, wherein the 3D feature includes at least one of;

a ridge shape, a ridge height, a valley depth, a valley shape, a ridge flow gradient, ridge height gradient;

generating 3D feature data for the 3D feature detected in the 3D surface map, wherein the 3D feature data includes 3D coordinates;

comparing the 3D feature data with a plurality of biometric 3D data sets, wherein each of the plurality of 3D biometric data sets includes 3D coordinates for at least one type of 3D feature;

generating a confidence value in response to a comparison between the 3D feature data and one of the plurality of biometric 3D data sets; and

determining a match between the 3D feature data and the one of the plurality of 3D biometric data sets when the confidence value exceeds a threshold, wherein one or more steps is performed using a processing module.

2. The method of claim 1, further comprising:

determining a relative distance and orientation angle between features in the 3D surface map;

receiving a relative distance and orientation angle between features based on a 2D binary image; and

comparing the relative distance and orientation angle between features in the 3D surface map with the relative distance and orientation angle between features based on the 2D binary image; and

generating a confidence value based on the comparison.