Biometric system for biometric input, comparison, authentication and access control and method therefor

• US 6,282,304 B1
• Filed: 05/14/1999
• Issued: 08/28/2001
• Est. Priority Date: 05/14/1999
• Status: Expired due to Fees

• Current Assignee: Compulink Research Incorporated
• Original Assignee: BioLink Technologies International, Inc.
• Inventors: Chernomordik, Oleg Mikhailovich, Novikov, Sergey Olegovich
• Primary Examiner(s): Au, Amelia
• Assistant Examiner(s): AHMED, SAMIR ANWAR
• Application Number:
  US09/312,002
• Time in Patent Office: 837 Days
• Field of Search: 382/115, 382/124, 382/125, 235/380, 235/492, 704/246, 704/273, 902/3, 902/41, 902/251, 340/5.52, 340/5.53, 340/5.82, 340/5.83, 283/68, 356/71, 703/1, 703/26, 703/42
• US Class Current: 382/125
• CPC Class Codes: G06F 21/32 using biometric data, e.g. fingerprints, iris scans or voiceprints
• CPC Class Codes: G06F 21/83 input devices, e.g. keyboards, mice or controllers thereof
• CPC Class Codes: G06F 2203/0336 Mouse integrated fingerprint sensor
• CPC Class Codes: G06F 3/03543 Mice or pucks G06F3/03541 takes precedence
• CPC Class Codes: G06V 40/12 Fingerprints or palmprints
• CPC Class Codes: G07C 9/37 using biometric data, e.g. fingerprints, iris scans or voice recognition

Abstract

A biometric input device, system and method includes a biometric input device having a scanning window surrounded by a ridge for ensuring positive positioning of a biometric sample such as a thumb. The biometric input device includes an optical assembly having a prism with a focusing lens disposed on a side thereof and optionally integrally formed therewith. A biometric comparison method is provided for comparing data from said biometric input device with data from a database using both directional image comparison and clusterized minutia location and direction comparison. A further system is provided for allowing access to computer functions base on the outcome of the comparison method.

Claims

1. A biometric comparison method comprising the steps of:

(a) scanning in a fingerprint to and digitizing scanning signals to produce a matrix of print image data representing pixels;

(b) dividing said print image data into cells, each including a number of pixel data for contiguous pixels;

(c) calculating a matrix of directional image data DI using gradient statistics applied to said cells wherein said directional image data DI includes for each of said cells a cell position indicator and one of a cell vector indicative of a direction of ridge lines and an undirectional flag indicative of a nondirectional calculation result;

(d) skeletonizing said print image data;

(e) extracting minutia from said print image data and producing a minutia data set comprised of data triplets for each minutia extracted including minutia position data and minutia direction data;

(f) providing reference fingerprint data from a database wherein said reference fingerprint data includes reference directional image data DI and a reference minutia data set;

(g) performing successive comparisons of said directional image data DI with said reference directional image data DI and determining a directional difference DifDI for each of said successive comparisons wherein for each of said successive comparisons one of said directional image data DI and said reference directional image data DI is positionally shifted by adding position shift data;

(h) determining for which of said successive comparisons said directional difference DifDI is the least and selecting said position shift data thereof as initial minutia shift data;

(i) positionally shifting minutia data by applying said initial minutia shift data to one of said minutia data set and said reference minutia data set to initially positionally shift said minutia position data and said minutia orientation data;

(j) performing successive comparisons of said minutia data set with said reference minutia data set following said positionally shifting minutia data and determining matching minutia based on a minutia distance criteria, a number of matching minutia, and a similarity measure indicative of correspondence of said matching minutia for each of said successive comparisons wherein, for each of said successive comparisons, one of said minutia data set and said reference minutia data set is positionally shifted within a minutia shift range R by adding minutia position shift data;

(k) determining a maximum similarity measure of said similarity measures of said successive comparisons; and

(l) determining whether said maximum similarity measure is above a similarity threshold and indicating said reference fingerprint data and said fingerprint data are from the same fingerprint when said maximum similarity measure is above said similarity threshold.

2. The biometric comparison method of claim 1 further comprising the steps of:

(c1) identifying as part of step (c) a directional group of cells comprising all cells of said cells that do not have said undirectional flag associated therewith; and

(j1) excluding from said successive comparisons in step (j) minutia of said minutia data set and said reference minutia data set located in or positionally aligned with said cells that have said undirectional flag associated therewith.

3. The biometric comparison method of claim 1 wherein:

step (j) includes;

dividing said minutia data set into said minutia data set clusters formed of contiguous one said cells and each including a predetermined number of said minutia before conducting said successive comparisons; and

conducting said successive comparisons for each of said minutia data set clusters and determining for each of said minutia data set clusters a maximum similarity measure; and

step (k) includes determining said maximum similarity measure as a sum of said maximum similarity measures of each of said minutia data set clusters.

4. The biometric comparison method of claim 1 wherein step (e) includes excluding from further processing pairs of said minutia located within a minutia exclusion distance of one another and having minutia direction data with a direction exclusion limit of being in opposite directions.

5. The biometric comparison method of claim 1 wherein said minutia extraction step (e) extracts minutia limited to ends and bifurcations.

6. The biometric comparison method of claim 1 wherein said minutia extraction step (e) wherein said minutia data set excludes data distinguishing ends and bifurcations.