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SE1751569A1 - Method and device for classifying fingerprint - Google Patents

Method and device for classifying fingerprint

Info

Publication number
SE1751569A1
SE1751569A1 SE1751569A SE1751569A SE1751569A1 SE 1751569 A1 SE1751569 A1 SE 1751569A1 SE 1751569 A SE1751569 A SE 1751569A SE 1751569 A SE1751569 A SE 1751569A SE 1751569 A1 SE1751569 A1 SE 1751569A1
Authority
SE
Sweden
Prior art keywords
features
image
fingerprint
verify
fingerprint image
Prior art date
Application number
SE1751569A
Inventor
David Tingdahl
Kenneth Jonsson
Original Assignee
Fingerprint Cards Ab
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Fingerprint Cards Ab filed Critical Fingerprint Cards Ab
Priority to SE1751569A priority Critical patent/SE1751569A1/en
Priority to CN201880016174.3A priority patent/CN110383283A/en
Priority to PCT/SE2018/051264 priority patent/WO2019125270A1/en
Publication of SE1751569A1 publication Critical patent/SE1751569A1/en

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/12—Fingerprints or palmprints
    • G06V40/1347—Preprocessing; Feature extraction
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
    • G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
    • G06V10/757—Matching configurations of points or features
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/12—Fingerprints or palmprints
    • G06V40/1365—Matching; Classification
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/40—Spoof detection, e.g. liveness detection

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Human Computer Interaction (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Artificial Intelligence (AREA)
  • Health & Medical Sciences (AREA)
  • Computing Systems (AREA)
  • Databases & Information Systems (AREA)
  • Evolutionary Computation (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Collating Specific Patterns (AREA)
  • Image Input (AREA)

Abstract

The present disclosure relates to a method for determining whether an obtained verify fingerprint image (31) is genuine or impostor compared with an enrolled fingerprint. The method comprises obtaining the verify fingerprint image of a finger by means of a fingerprint sensor; extracting features from the verify fingerprint image; retrieving a stored template of features of at least one enrol image (32) of the enrolled fingerprint; matching the extracted features to a geometrical transform of the features of the template, wherein positive matches between the extracted features and the template features are determined to be inlying matches (34); determining an area of overlap (33) between the verify fingerprint image and the enrol image; and classifying the verify fingerprint image as genuine or impostor based on the number of the inlying matches in relation to the determined area of overlap.
SE1751569A 2017-12-18 2017-12-18 Method and device for classifying fingerprint SE1751569A1 (en)

Priority Applications (3)

Application Number Priority Date Filing Date Title
SE1751569A SE1751569A1 (en) 2017-12-18 2017-12-18 Method and device for classifying fingerprint
CN201880016174.3A CN110383283A (en) 2017-12-18 2018-12-10 Method and apparatus for fingerprint of classifying
PCT/SE2018/051264 WO2019125270A1 (en) 2017-12-18 2018-12-10 Method and device for classifying fingerprint

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
SE1751569A SE1751569A1 (en) 2017-12-18 2017-12-18 Method and device for classifying fingerprint

Publications (1)

Publication Number Publication Date
SE1751569A1 true SE1751569A1 (en) 2019-06-19

Family

ID=66998028

Family Applications (1)

Application Number Title Priority Date Filing Date
SE1751569A SE1751569A1 (en) 2017-12-18 2017-12-18 Method and device for classifying fingerprint

Country Status (3)

Country Link
CN (1) CN110383283A (en)
SE (1) SE1751569A1 (en)
WO (1) WO2019125270A1 (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021222917A1 (en) * 2020-04-29 2021-11-04 Qualcomm Incorporated Fingerprint sensor with detection of latent fingerprints
US20220327189A1 (en) * 2021-04-09 2022-10-13 Qualcomm Incorporated Personalized biometric anti-spoofing protection using machine learning and enrollment data

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6778685B1 (en) * 1999-07-08 2004-08-17 Nanyang Technological University Two-stage local and global fingerprint matching technique for automated fingerprint verification/identification
US20160042247A1 (en) * 2014-08-11 2016-02-11 Synaptics Incorporated Multi-view fingerprint matching
WO2016127736A1 (en) * 2015-02-13 2016-08-18 比亚迪股份有限公司 Computing method for area of fingerprint overlapping area and electronic apparatus

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101237148B1 (en) * 2011-04-06 2013-02-25 조선대학교산학협력단 Hierarchical fingerprint verification apparatus and method using similarity distribution
CN104463129B (en) * 2014-12-17 2018-03-02 浙江维尔科技股份有限公司 A kind of fingerprint register method and device
CN105447436B (en) * 2014-12-19 2017-08-04 比亚迪股份有限公司 Fingerprint identification system, fingerprint identification method, and electronic device

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6778685B1 (en) * 1999-07-08 2004-08-17 Nanyang Technological University Two-stage local and global fingerprint matching technique for automated fingerprint verification/identification
US20160042247A1 (en) * 2014-08-11 2016-02-11 Synaptics Incorporated Multi-view fingerprint matching
WO2016127736A1 (en) * 2015-02-13 2016-08-18 比亚迪股份有限公司 Computing method for area of fingerprint overlapping area and electronic apparatus

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
JEA T-Y et al. "A minutia-based partial fingerprint recognition system", PATTERN RECOGNITION , 2005-10-01, ELSEVIER, GB, nr. 10, Vol. 38, p. 1672-1684, ISSN 0031-3203 *
LOMTE ARCHANA C "Biometric fingerprint authentication with minutiae using ridge feature extraction", 2015 International Conference on Pervasive Computing (ICPC), 2015-01-08, IEEE, p. 1-6, ISBN: 978-1-4799-6272-3 *

Also Published As

Publication number Publication date
CN110383283A (en) 2019-10-25
WO2019125270A1 (en) 2019-06-27

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