IP Library Granted Patent US 9,858,465
Granted Patent B2
US 9,858,465 · App. 15/117,934 · Granted Jan 2, 2018

Electronic device comprising minimum sensing area and fingerprint information processing method thereof

Inventors: Baek Bum Pyun (Seoul, KR); Woo Taek Lim (Seoul, KR); Sung Chan Park (Seoul, KR); Jae Han Kim (Seongnam-si, KR)
Assignees: CRUCIALTEC CO., LTD.; CANVASBIO CO., LTD.
G06K9/00067G06K9/00013G06K9/00073G06K9/40G06T5/002G06T5/20
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Quick Facts
Patent No.
US 9,858,465
App. No.
15/117,934
Granted
Jan 2, 2018
Kind
B2
Abstract

According to one embodiment, provided is a method by which an electronic device comprising a minimum fingerprint sensing area processes fingerprint information, comprising the steps of: acquiring a fingerprint image from the fingerprint sensing area; calculating a shade change value, defined by a shade difference value from a neighboring pixel, for each pixel of the fingerprint image; selecting points, as feature point candidates, of which the shade change value is a threshold value or more; applying artificial distortion for noise filtering to an area including the feature point candidates and neighboring pixels thereof; and selecting, as final feature points, candidates of which the shade change value after the artificial distortion is within a threshold range from among the feature point candidates.

Claims (20)

1. A fingerprint information processing method for an electronic device including a minimum fingerprint sensing area, the method comprising:

acquiring a fingerprint image from the fingerprint sensing area;

calculating an intensity variation value defined as an intensity difference value with respect to a neighboring pixel for each pixel of the fingerprint image;

selecting points, each of which the intensity variation value is a threshold value or more, as feature point candidates;

applying artificial distortion to a region including the feature point candidates and neighboring pixels thereof for noise filtering; and

selecting candidates, each of which the intensity variation value after the artificial distortion is within a threshold range, among the feature point candidates as final feature points.

2. The method of claim 1 , further comprising performing fingerprint identification by comparing the final feature points with feature points of a preregistered fingerprint.

3. The method of claim 2 , wherein the performing of the fingerprint identification includes comparing an intensity variation vector having an intensity variation value and an intensity variation direction at each of the final feature points with an intensity variation vector at each of the feature points of the preregistered fingerprint.

4. The method of claim 3 , wherein the performing of the fingerprint identification further includes, before the comparing, selecting a target portion to be compared by comparing locations of the final feature points and the feature points of the preregistered fingerprint.

5. The method of claim 1 , further comprising casting each intensity variation value and mutual location information of the final feature points into a template format for storing.

6. The method of claim 1 , further comprising storing at least one of an intensity variation vector including an intensity variation value and an intensity variation direction and types of the feature points in the final feature points.

7. The method of claim 1 , wherein the applying of the artificial distortion includes applying a Gaussian filter to a region including the feature point candidates and the neighboring pixels thereof.

8. An electronic device comprising:

a fingerprint sensor which scans a fingerprint of a finger in contact with a minimum fingerprint sensing area to acquire a fingerprint image; and

an information processing device which performs:

calculating an intensity variation value defined as an intensity difference value from a neighboring pixel for each pixel of the fingerprint image;

selecting points, each of which the intensity variation value is equal to or more than a threshold value, as feature point candidates; and

selecting candidates, each of which the intensity variation value after the artificial distortion for noise filtering is within a threshold range, among the feature point candidates as final feature points.

9. The device of claim 8 , wherein the information processing device includes a fingerprint identification unit which performs fingerprint identification by comparing an intensity variation vector including an intensity variation value and an intensity variation direction at each of the final feature points with an intensity variation vector at each of the feature points of a preregistered fingerprint.

10. The device of claim 8 , wherein the information processing device includes a fingerprint registration unit which casts each intensity variation value and mutual location information of the final feature points into a template format for storing.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 3, 2019
From: THE KOREA DEVELOPMENT BANK
To: CRUCIALTEC CO., LTD.
Reel/Frame 047896/0300 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 1, 2018
From: CRUCIALTEC CO., LTD.; CANVASBIO CO., LTD.
To: THE KOREA DEVELOPMENT BANK
Reel/Frame 045687/0050 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 10, 2016
From: PYUN, BAEK BUM; LIM, WOO TAEK; PARK, SUNG CHAN; KIM, JAE HAN
To: CRUCIALTEC CO., LTD.; CANVASBIO CO., LTD.
Reel/Frame 039397/0134 →
Priority Claims (2)
KR 10-2014-0017512 · Feb 14, 2014 · national
KR 10-2014-0065418 · May 29, 2014 · national
Continuity (1)
Related Publication 20160350580A1 · Dec 1, 2016