FR3109457B1 - Procédé de détection d’attaque par présentation pour des empreintes digitales - Google Patents

Procédé de détection d’attaque par présentation pour des empreintes digitales Download PDF

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Publication number
FR3109457B1
FR3109457B1 FR2003840A FR2003840A FR3109457B1 FR 3109457 B1 FR3109457 B1 FR 3109457B1 FR 2003840 A FR2003840 A FR 2003840A FR 2003840 A FR2003840 A FR 2003840A FR 3109457 B1 FR3109457 B1 FR 3109457B1
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France
Prior art keywords
fingerprints
detection method
attack detection
presentation attack
presentation
Prior art date
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Active
Application number
FR2003840A
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English (en)
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FR3109457A1 (fr
Inventor
Joannes Falade
Sandra Cremer
Christophe Rosenberger
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Imprimerie Nationale
Original Assignee
Imprimerie Nationale
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Filing date
Publication date
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Priority to FR2003840A priority Critical patent/FR3109457B1/fr
Priority to PCT/EP2021/059492 priority patent/WO2021209412A1/fr
Priority to EP21717098.4A priority patent/EP4136565A1/fr
Publication of FR3109457A1 publication Critical patent/FR3109457A1/fr
Application granted granted Critical
Publication of FR3109457B1 publication Critical patent/FR3109457B1/fr
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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06V40/1382—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger
    • G06V40/1388—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger using image processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2411—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on the proximity to a decision surface, e.g. support vector machines
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/54—Extraction of image or video features relating to texture
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06V10/758—Involving statistics of pixels or of feature values, e.g. histogram matching
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/98—Detection or correction of errors, e.g. by rescanning the pattern or by human intervention; Evaluation of the quality of the acquired patterns
    • G06V10/993—Evaluation of the quality of the acquired pattern
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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; CALCULATING OR 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; CALCULATING OR 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/46—Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
    • G06V10/467—Encoded features or binary features, e.g. local binary patterns [LBP]

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Human Computer Interaction (AREA)
  • Evolutionary Computation (AREA)
  • Data Mining & Analysis (AREA)
  • Artificial Intelligence (AREA)
  • Quality & Reliability (AREA)
  • General Health & Medical Sciences (AREA)
  • Databases & Information Systems (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Computing Systems (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • General Engineering & Computer Science (AREA)
  • Collating Specific Patterns (AREA)
  • Image Analysis (AREA)

Abstract

L’invention concerne un procédé et un système de détection d’attaque par présentation d’empreintes sur un capteur adapté dans lequel on concatène un vecteur texture et un vecteur métier pour construire un modèle permettant de discriminer les empreintes réelles des empreintes factices. Figure 1
FR2003840A 2020-04-16 2020-04-16 Procédé de détection d’attaque par présentation pour des empreintes digitales Active FR3109457B1 (fr)

Priority Applications (3)

Application Number Priority Date Filing Date Title
FR2003840A FR3109457B1 (fr) 2020-04-16 2020-04-16 Procédé de détection d’attaque par présentation pour des empreintes digitales
PCT/EP2021/059492 WO2021209412A1 (fr) 2020-04-16 2021-04-13 Procede de detection d'attaque par presentation pour des empreintes digitales
EP21717098.4A EP4136565A1 (fr) 2020-04-16 2021-04-13 Procede de detection d'attaque par presentation pour des empreintes digitales

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FR2003840A FR3109457B1 (fr) 2020-04-16 2020-04-16 Procédé de détection d’attaque par présentation pour des empreintes digitales
FR2003840 2020-04-16

Publications (2)

Publication Number Publication Date
FR3109457A1 FR3109457A1 (fr) 2021-10-22
FR3109457B1 true FR3109457B1 (fr) 2023-03-24

Family

ID=72088228

Family Applications (1)

Application Number Title Priority Date Filing Date
FR2003840A Active FR3109457B1 (fr) 2020-04-16 2020-04-16 Procédé de détection d’attaque par présentation pour des empreintes digitales

Country Status (3)

Country Link
EP (1) EP4136565A1 (fr)
FR (1) FR3109457B1 (fr)
WO (1) WO2021209412A1 (fr)

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8090163B2 (en) * 2006-10-10 2012-01-03 West Virginia University Research Corp. Multi-resolutional texture analysis fingerprint liveness systems and methods

Also Published As

Publication number Publication date
FR3109457A1 (fr) 2021-10-22
EP4136565A1 (fr) 2023-02-22
WO2021209412A1 (fr) 2021-10-21

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